Parking charging facility intelligent scheduling method and system based on life cycle management
By using lifecycle management methods, vehicle demand is recorded and the health status of parking spaces and charging piles is assessed to generate intelligent scheduling solutions. This solves the problems of resource waste and poor user experience in existing technologies and achieves efficient management of parking and charging facilities.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- AI SUPER EYE TECH CO LTD
- Filing Date
- 2026-03-12
- Publication Date
- 2026-06-05
Smart Images
Figure CN122155028A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of intelligent parking technology, specifically to an intelligent scheduling method and system for parking and charging facilities based on lifecycle management. Background Technology
[0002] With the advancement of urbanization, the number of parking spaces and charging piles is constantly increasing, which puts forward higher requirements for the management and scheduling of parking and charging facilities. How to efficiently and intelligently schedule limited parking spaces and charging pile resources to ensure that electric vehicle users can find parking and charging locations in a timely manner is an urgent problem to be solved.
[0003] Many existing parking and charging facilities still rely on manual maintenance or simple periodic inspections for scheduling, failing to fully utilize equipment lifecycle data and health status assessments. This results in the inability to monitor and manage the health status of parking and charging facilities in real time, leading to frequent malfunctions during operation. Damage to charging piles or parking spaces is often not detected in advance. This lack of effective health management means that users may encounter damaged or unusable facilities when looking for charging piles, thus affecting user experience, reducing facility utilization efficiency, and increasing maintenance costs. Summary of the Invention
[0004] This application provides a smart scheduling method and system for parking and charging facilities based on lifecycle management, aiming to solve the technical problem that most existing parking and charging facility scheduling methods rely on simple periodic inspections, lacking in-depth analysis of facility usage status, resulting in the failure to monitor and manage the health status of facilities in real time, thus affecting the scheduling efficiency of parking and charging facilities.
[0005] The first aspect disclosed in this application provides an intelligent scheduling method for parking and charging facilities based on lifecycle management. The method includes: when a target vehicle enters a target parking area, recording the parking start time and interactively acquiring the parking and charging demand information of the target vehicle, wherein the parking and charging demand information includes parking duration and charging demand; acquiring M parking space units and N charging pile units in the target parking area, where M > N; starting from the parking start time, based on predetermined lifecycle nodes, backtracking the full lifecycle datasets of the M parking spaces and N charging piles, as well as historical environmental datasets; based on the full lifecycle datasets of the M parking spaces, N charging piles, and historical environmental datasets, performing a health status assessment of the parking and charging facilities, and outputting health status characteristics of the M parking spaces and N charging piles; performing parking and charging facility scheduling analysis based on the health status characteristics of the M parking spaces and N charging piles, as well as the parking duration and charging demand, and generating a parking and charging facility scheduling plan; generating parking and charging guidance information based on the parking and charging facility scheduling plan and sending it to the target vehicle.
[0006] The second aspect of this application discloses an intelligent scheduling system for parking and charging facilities based on lifecycle management. This system is used in the aforementioned intelligent scheduling method for parking and charging facilities based on lifecycle management. The system includes: a parking and charging demand acquisition module, used to record the parking start time when a target vehicle enters a target parking area and interactively acquire the parking and charging demand information of the target vehicle, wherein the parking and charging demand information includes parking duration and charging demand; a parking space unit acquisition module, used to acquire M parking space units and N charging pile units in the target parking area, wherein M > N; and a lifecycle data backtracking module, used to backtrack the M parking space units and N charging piles based on predetermined lifecycle nodes, starting from the parking start time. The unit includes a dataset of the entire lifecycle of M parking spaces and N charging piles, as well as a historical environmental dataset; a health status assessment module, used to assess the health status of parking and charging facilities based on the datasets of the entire lifecycle of the M parking spaces, N charging piles, and historical environmental datasets, and output the health status characteristics of the M parking spaces and N charging piles; a facility scheduling analysis module, used to perform parking and charging facility scheduling analysis based on the health status characteristics of the M parking spaces, N charging piles, parking duration, and charging demand, and generate a parking and charging facility scheduling plan; and a parking and charging guidance module, used to generate parking and charging guidance information based on the parking and charging facility scheduling plan and send it to the target vehicle.
[0007] One or more technical solutions provided in this application have at least the following beneficial effects:
[0008] Interactive acquisition of vehicle demand information ensures accurate identification of the target vehicle's specific parking duration and charging needs, improving service personalization and targeting. Acquiring parking space and charging pile units within the parking area ensures a clear understanding of the configuration of parking spaces and charging piles within the target parking area, avoiding conflicts or resource waste. Based on lifecycle data, a comprehensive assessment of the health status of parking spaces and charging piles provides comprehensive data support for scheduling decisions. Real-time monitoring of parking space and charging pile usage through health status assessment provides a more accurate basis for resource allocation during the scheduling process, prioritizing facilities with better health to improve parking and charging efficiency and safety. Intelligent scheduling analysis integrates the health status of parking spaces and charging piles, vehicle parking duration, and charging needs to achieve refined scheduling. Comprehensive analysis of multi-dimensional data can significantly improve facility utilization efficiency and avoid resource waste. Generating accurate guidance information ensures that target vehicles quickly find available parking spaces and charging piles, avoiding wasted time searching for parking locations and improving overall resource utilization efficiency.
[0009] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description
[0010] Figure 1 A schematic diagram of the intelligent scheduling method for parking and charging facilities based on lifecycle management provided in this application embodiment.
[0011] Figure 2 A schematic diagram of the structure of an intelligent scheduling system for parking and charging facilities based on lifecycle management, provided in an embodiment of this application.
[0012] Explanation of reference numerals in the attached diagram: 10 for parking and charging demand acquisition module, 20 for parking space unit acquisition module, 30 for lifecycle data backtracking module, 40 for health status assessment module, 50 for facility scheduling and analysis module, and 60 for parking and charging guidance module. Detailed Implementation
[0013] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.
[0014] Example 1, as Figure 1As shown in the embodiments of this application, an intelligent scheduling method for parking and charging facilities based on lifecycle management is provided, the method comprising:
[0015] When a target vehicle enters the target parking area, the parking start time is recorded, and the parking and charging demand information of the target vehicle is obtained interactively. The parking and charging demand information includes the parking duration and the charging amount required.
[0016] When a target vehicle enters the target parking area, the system first identifies the vehicle and initiates the dispatch process. Sensors, cameras, and license plate recognition technology are used to confirm the vehicle's identity and the time of its entry into the parking area. The parking start time is automatically recorded based on the vehicle's entry time, serving as the starting point for subsequent parking and charging management to ensure accurate calculation of data such as charging duration and parking duration. Through interaction with the vehicle, the system obtains specific parking and charging requirements. Parking duration refers to the expected parking time, and charging demand refers to the amount of electricity the vehicle needs to charge, measured in kWh (kilowatt-hours).
[0017] Obtain M parking space units and N charging pile units in the target parking area, where M > N.
[0018] Identify available parking spaces and charging piles within the target parking area. Since there are more parking spaces than charging piles (M>N), this means that there may be parking spaces without charging piles, or multiple vehicles sharing a single charging pile. Especially when charging pile resources are scarce, this information on the distribution of parking spaces and charging piles is provided by the parking management system or related hardware facilities.
[0019] Starting from the parking start time, based on predetermined lifecycle nodes, backtrack the M parking space units and N charging pile units to obtain the full lifecycle datasets of the M parking spaces and N charging piles, as well as the historical environment dataset.
[0020] The predetermined lifecycle nodes refer to the various lifecycle stages of parking spaces and charging piles, including construction, commissioning, operation, maintenance, and decommissioning. Based on these nodes, the full lifecycle datasets for parking spaces and charging piles are traced back. These datasets include detailed data for each lifecycle stage. For example, the parking space full lifecycle dataset includes various data from the construction, commissioning, operation, and maintenance stages of parking spaces, such as usage frequency, maintenance records, and fault records. The charging pile full lifecycle dataset includes data from the construction, commissioning, maintenance, and decommissioning of charging piles, recording information such as equipment status, maintenance history, and charging performance. Historical environmental datasets related to the parking area are also traced back. These datasets contain information related to environmental factors, such as ambient temperature, humidity, climate change, traffic flow, and regional safety conditions. This environmental data is used to assess the health status of parking and charging facilities, as these factors can affect the operational performance and lifespan of the facilities.
[0021] Based on the M parking space full life cycle datasets, N charging pile full life cycle datasets, and historical environment datasets, a health status assessment of parking and charging facilities is conducted, outputting the health status characteristics of M parking spaces and N charging piles.
[0022] By analyzing the entire lifecycle dataset of parking spaces, health status characteristics are extracted. This dataset includes data on the construction, commissioning, operation, maintenance, and decommissioning stages of parking spaces. The health status of parking spaces is assessed based on this data, using metrics such as health scores and performance indicators to derive the health status characteristics of each space. Similarly, the entire lifecycle dataset of charging piles contains data on the construction, commissioning, operation, and maintenance stages. Health status characteristics of charging piles are generated based on this data, similar to the health assessment of parking spaces, using health score calculations to provide a health status score for each charging pile. Environmental factors affect the usage and performance of parking spaces and charging piles. Historical environmental datasets are used to further optimize health status assessments. Environmental data influences the aging rate of equipment or has other impacts, such as the effect of temperature changes on batteries. Based on the above assessment process, health status characteristics are output for each parking space and charging pile. These health status characteristics serve as input for subsequent scheduling decisions, helping to optimize the allocation of parking and charging resources.
[0023] Based on the health status characteristics of the M parking spaces, the health status characteristics of the N charging piles, and the parking duration and charging demand, a parking and charging facility scheduling analysis is performed to generate a parking and charging facility scheduling plan.
[0024] The parking and charging facility scheduling analysis is based on the following factors: the health scores of parking spaces and charging stations determine which facilities can be scheduled and which should be avoided; parking duration and charging demand limit the number and type of parking spaces and charging stations that can be allocated. Based on these characteristics and demands, optimization algorithms, such as linear programming and heuristic algorithms, are used to generate the optimal parking and charging facility scheduling scheme, ensuring that vehicles can park and charge in healthy parking spaces and charging stations while meeting demand.
[0025] Parking and charging guidance information is generated based on the parking and charging facility scheduling plan and sent to the target vehicle.
[0026] The parking and charging facility scheduling scheme identifies available parking spaces and charging stations for the target vehicle, generating parking and charging guidance information, including parking space locations, charging station locations, and route directions. This information is transmitted to the target vehicle in real time via wireless communication, such as in-vehicle systems and mobile applications. The target vehicle can then see the specific locations of parking spaces and charging stations, as well as the driving route, through its in-vehicle navigation system, ensuring efficient and smooth parking and charging.
[0027] Furthermore, the predetermined life cycle nodes are divided according to the life cycle status attributes of the M parking space units and N charging pile units. The predetermined life cycle nodes include construction nodes, commissioning nodes, operation nodes, maintenance nodes, and decommissioning nodes.
[0028] The construction node marks the transition from planning to actual construction of parking spaces and charging piles. This node signifies the completion of the physical infrastructure of the parking space or charging pile and its readiness for use. The commissioning node marks the point at which parking spaces and charging piles begin to be used. At this time, the facilities have been completed and passed the necessary acceptance tests, and are open to users. The operation node marks the stage where parking spaces and charging piles are in normal use during long-term operation. The facilities should operate efficiently and undergo regular inspections and maintenance. The maintenance node marks the stage where the facilities require regular repairs and maintenance. This node signifies that the facilities have entered a periodic maintenance phase, with the aim of extending the service life of the facilities. The obsolescence node marks the point when parking spaces or charging piles reach the end of their service life or when the technology no longer meets the requirements. At this time, the facilities will be obsolete, no longer used, and will be scrapped, dismantled, or replaced.
[0029] Furthermore, this includes:
[0030] For the M parking space units, parking space and supporting data, parking space commissioning initialization data, parking space operation behavior data, and parking space operation and maintenance data are collected from the construction node, commissioning node, operation node, and maintenance node, respectively, and integrated to obtain the M parking space full life cycle dataset. For the N charging pile units, charging pile equipment and electrical configuration data, charging pile commissioning initialization data, charging pile operation behavior data, and charging pile operation and maintenance data are collected from the construction node, commissioning node, operation node, and maintenance node, respectively, and integrated to obtain the N charging pile full life cycle dataset. For any parking space unit and any charging pile unit in the elimination node, an unusable mark is made, and elimination archive data is collected and added to the M parking space full life cycle dataset and the N charging pile full life cycle dataset.
[0031] During the construction phase, data on the spatial layout, design, and supporting facilities of parking spaces, such as safety measures, markings, and lighting, are collected. This data is used to subsequently evaluate the actual use and space utilization of the parking spaces. After the parking spaces are put into operation, the initial usage is recorded, including the initial state at the time of commissioning, such as occupancy rate, space size, and facility configuration. During the operation phase, actual usage behavior is recorded, including occupancy rate, parking duration, parking demand, and frequency of use. During the maintenance phase, maintenance records are kept, including repair records, equipment upgrades, and the impact of environmental factors on the parking spaces. This data indicates the wear and tear of the parking space facilities.
[0032] During the construction phase, data on the charging pile's equipment configuration, such as charging power, electrical connections, charging pile model, and charging socket type, should be collected. After the charging pile is put into operation, its initial operating status should be recorded, including initial availability, system initialization configuration, and whether the charging function is normal after commissioning. During operation, the charging pile's working status should be continuously monitored, including charging frequency, charging power, equipment failures, charging duration, and utilization rate. The maintenance process of the charging pile should be recorded, including repairs, maintenance, and equipment and software updates, with a focus on whether there are frequent failures or performance degradations throughout the equipment's lifecycle.
[0033] A phase-out node indicates that a parking space or charging station has reached the end of its service life or is no longer suitable for continued use due to other reasons, such as excessively high failure rates or outdated technology. When a parking space or charging station enters the phase-out node, the facility is marked as unavailable and is no longer allowed to participate in scheduling. Detailed information about the facility's phase-out is recorded, such as the reason for phase-out (e.g., equipment failure, aging, replacement), and the phase-out date. This phase-out archived data is integrated into the full lifecycle dataset of parking spaces and charging stations for historical data review and analysis.
[0034] Furthermore, a health assessment of parking and charging facilities should be conducted, including:
[0035] Lifecycle features are extracted from the M parking space full lifecycle datasets to construct a parking space operation feature set; lifecycle features are extracted from the N charging pile full lifecycle datasets to construct a charging pile operation feature set; environmental impact features are extracted from the historical environment datasets to construct an environmental impact feature set; based on the parking space operation feature set, the charging pile operation feature set, and the environmental impact feature set, a facility health assessment index system is constructed; based on the facility health assessment index system, the health status of the M parking space units and the N charging pile units is calculated to obtain M parking space health status indicators and M charging pile health status indicators; corresponding health status features are extracted from the M parking space health status indicators and the M charging pile health status indicators to generate the M parking space health status features and the N charging pile health status features.
[0036] This study extracts features related to parking space operation from the entire lifecycle dataset of parking spaces. These features include: the usage frequency of parking spaces, such as the average number of parking visits or occupancy rate of each space within a certain period; the parking duration of vehicles in parking spaces, including average parking time and peak-hour parking duration; the load status of parking spaces, such as peak-hour parking demand and vacancy rate; and the physical wear and tear and maintenance frequency of parking spaces, such as the number of maintenance and repairs, as well as damage that occurs during use, such as blurred markings and ground damage. The extracted features are then organized and integrated to form a parking space operation feature set. These features provide the foundational data for subsequent health assessments, indicating which parking spaces are operating well and which have problems, such as aging or damaged facilities.
[0037] Feature information related to the operation of charging piles is extracted from the full lifecycle dataset. This includes: extracting the usage frequency of charging piles, such as the number of charging times per day or per month; extracting the charging power characteristics of each charging pile, including charging speed, such as the power range supported by the charging pile, and the actual charging power usage; extracting fault data, maintenance frequency, and repair history of charging piles, including equipment failures, communication problems, and electrical problems; and extracting equipment wear, including the aging degree of the charging pile equipment, wear of charging cables, and wear of sockets. The extracted feature data is integrated into a charging pile operation feature set, which contains key data such as the usage status, fault history, and equipment performance of charging piles, providing a basis for subsequent health assessments.
[0038] Features related to the impact of the environment on parking spaces and charging stations were extracted from historical environmental datasets. These environmental factors affect the performance, wear and tear, and health of the facilities, including: ambient temperature, which affects the aging rate of equipment and facilities in parking spaces and charging stations (e.g., excessively high or low temperatures accelerate battery aging and damage to charging station equipment); air pollution and humidity, which affect the surface condition of parking spaces and even the performance of electrical components in charging stations (e.g., high pollution accelerates corrosion of parking space and charging station equipment); and traffic flow, which affects the frequency and duration of parking space use, thus impacting the facility's load. Parking spaces in high-traffic areas are used frequently, accelerating wear and tear. After extracting these environmental impact features, they were integrated into an environmental impact feature set to indicate the impact of external environmental factors on parking and charging facilities for further health status assessment.
[0039] Based on the above set of features, a facility health assessment index system is established. This system integrates various aspects such as the operating status of parking spaces and charging piles, the health status of equipment, and the impact of environmental factors on the facilities. Through the health assessment index system, the health status of parking spaces and charging piles can be dynamically assessed.
[0040] Based on the facility health assessment index system, the health score of each parking space is calculated. Specifically, different lifecycle characteristics are assigned different weights according to their degree of influence; for example, wear and tear has a higher weight, followed by operating frequency and maintenance records. The health score of the parking space is calculated by weighting each characteristic. Similarly, the health score of charging piles is calculated based on their lifecycle characteristics.
[0041] Based on the health index of parking spaces, the status of parking spaces is determined. Similar to parking spaces, charging piles are divided into different health states according to their health scores. Based on the health scores and set thresholds, corresponding health state features are generated for each parking space and charging pile, forming a set of parking space health state features and a set of charging pile health state features. These features serve as key factors in subsequent scheduling analysis, affecting resource allocation and scheduling.
[0042] Furthermore, the process involves analyzing the scheduling of parking and charging facilities to generate a scheduling plan, including:
[0043] Based on the parking duration and charging demand, candidate parking space units and candidate charging pile units that meet the parking duration and charging capacity constraints are selected from the M parking space units and N charging pile units. Based on these candidate sets, a parking-charging combination set is constructed, and a parking-charging matching relationship matrix is established according to the spatial proximity, binding, or service radius relationship between parking spaces and charging piles. For each parking-charging combination in the matching relationship matrix, a facility health score is calculated based on the corresponding parking space health status characteristics and charging pile health status characteristics, and a service matching score is calculated based on the parking duration and charging demand. The facility health score and service matching score are weighted and fused to generate a scheduling priority score for each parking-charging combination. The target parking space unit and target charging pile unit are located based on the scheduling priority score to generate the parking-charging facility scheduling scheme.
[0044] Parking spaces that meet the expected parking duration requirements of the target vehicle are selected. If a parking space is in good condition and no other vehicle is currently occupying it for more than the expected parking duration, it will be considered a candidate parking space. Charging stations are then selected based on the target vehicle's charging needs, such as the required charging capacity or charging time. The charging station's charging capabilities, such as maximum charging power and charging speed, must meet the target vehicle's charging needs. After selecting parking spaces and charging stations that meet the parking duration and charging demand constraints, these parking spaces and charging stations are grouped into candidate sets, namely, a candidate parking space unit set and a candidate charging station unit set.
[0045] The candidate parking space unit set and the candidate charging pile unit set are combined to generate all possible parking-charging combinations. Each combination includes one parking space and one charging pile, ensuring that the parking and charging needs of the target vehicle can be met. Spatial proximity indicates whether the parking space and charging pile are located in the same location or whether the distance between them is appropriate. Spatial proximity is an important matching criterion. If the parking space and charging pile are too far apart, it will increase the travel time of the target vehicle and reduce the service experience. Binding relationship refers to some parking spaces being bound to specific charging piles, or some charging piles only providing charging services for specific types of vehicles. Therefore, matching is based on the binding relationship between parking spaces and charging piles. Service radius relationship refers to the service radius of the charging pile, that is, its effective coverage area. Only parking spaces within this radius can use the charging pile, which is determined based on the type of charging pile (such as DC fast charging, AC slow charging, etc.) and physical layout. Based on the spatial proximity relationship, binding relationship, and service radius relationship between parking spaces and charging piles, a parking-charging matching relationship matrix is constructed. This matrix indicates whether each parking space and each charging pile can be matched, and a weight can be assigned to each match based on factors such as distance and binding.
[0046] Based on the target vehicle's parking duration and charging demand, a service matching score is calculated for each parking-charging combination. For example, if the parking duration and charging demand are well matched, the combination has a high service matching score; conversely, if the parking space's vacancy time does not match the vehicle's parking duration, or if the charging station's charging capacity cannot meet the vehicle's needs, the service matching score is low. The health scores of the parking space and charging station are combined with the service matching score to obtain a comprehensive score for each parking-charging combination. This process indicates which combinations are best suited to the current vehicle's needs and which combinations have health issues or do not meet the vehicle's requirements.
[0047] Based on actual needs, appropriate weights are assigned to facility health scores and service matching scores. For example, facility health is given a higher weight because unhealthy facilities cannot provide stable services. The facility health scores and service matching scores are weighted and merged to generate a scheduling priority score for each parking and charging combination. Combinations with high priority scores are the optimal choices under the condition of meeting health status and service requirements.
[0048] Based on the scheduling priority score of each parking-charging combination, all candidate combinations are ranked, and the parking-charging combination with the highest score is selected. The target parking space unit and target charging pile unit are then determined, assigning the optimal parking and charging location to the target vehicle. A parking-charging facility scheduling plan is generated, which includes information such as the specific locations of parking spaces and charging piles, route guidance, and expected charging times.
[0049] Furthermore, it also includes:
[0050] Obtain real-time resource occupancy information and queuing information for the target parking area, calculate resource availability scores for each parking and charging combination, and adjust the scheduling priority scores accordingly.
[0051] Real-time resource occupancy and queuing information for the target parking area is obtained to more accurately assess the availability of parking spaces and charging stations. Real-time resource occupancy information includes parking space occupancy, charging station occupancy, and resource availability. Queueing information is used to assess whether the target vehicle needs to queue and the length of the wait. A resource availability score is calculated for each parking-charging combination. The scoring is based on the following criteria: a higher score is given if both parking spaces and charging stations are vacant; a lower score is given if there is queuing or resource occupancy.
[0052] The initial scheduling priority score is adjusted based on the resource availability score. For example, if the resource availability of a combination is low, such as long queuing time or parking spaces / charging piles being occupied, the priority score of that combination is reduced to avoid scheduling the target vehicle to combinations with limited available resources. This compensation adjustment is dynamic and is recalculated every time the resource status changes, ensuring that the scheduling decision can reflect the current resource changes in real time.
[0053] Furthermore, it also includes:
[0054] Upon receiving a parking and charging reservation request, the system connects to the digital transportation platform to obtain real-time traffic data, including real-time traffic flow, road congestion index, vehicle speed, and road event information around the target parking area. Based on the real-time traffic data, the system calculates the estimated travel time for the reserved vehicle to reach each parking and charging combination, generating an arrival efficiency score. It then obtains the reservation scheduling priority score for the reserved vehicle. The system merges the arrival efficiency score and the reservation scheduling priority score to obtain a parking and charging reservation scheduling score. Finally, based on the parking and charging reservation scheduling score, the system determines the reserved parking space unit and the reserved charging pile unit, generating a parking and charging reservation facility scheduling plan.
[0055] Upon receiving a vehicle's reserved parking and charging information, the system connects to the digital transportation platform to obtain real-time traffic data from surrounding roads, including: real-time traffic flow data, which is the number of vehicles passing through the area within a specific time period, used to determine whether traffic conditions are busy, thus affecting the time it takes for vehicles to arrive at the parking area; road congestion index, used to assess whether the reserved vehicle will be delayed in arriving at the target parking area due to traffic reasons; vehicle speed, a decrease in speed means that the vehicle will need more time to reach the target parking area; and road event information, such as traffic accidents, road closures, construction, etc., which have a direct impact on traffic flow and speed.
[0056] Based on the current location of the reserved vehicle and the location of the target parking area, the estimated travel time is calculated in conjunction with real-time traffic conditions. Factors such as traffic flow, road congestion, and road speed are considered to determine the time required for the vehicle to reach the parking and charging station. An arrival efficiency score is generated based on the calculated estimated travel time; a shorter estimated travel time results in a higher efficiency score, and vice versa.
[0057] Using the same method as described above, the reservation scheduling priority score of the reserved vehicle is obtained based on the facility health score and service matching score.
[0058] The arrival efficiency score and the reservation scheduling priority score are combined for fusion calculation. In order to obtain the most suitable scheduling scheme, different weights are assigned to these two scores. For example, if traffic conditions have a greater impact on scheduling, the arrival efficiency score is given a higher weight. The reservation parking and charging scheduling score reflects the overall priority of each reservation parking and charging combination. Through this score, it is possible to identify which combinations are most suitable to be scheduled to reserved vehicles. Combinations with higher scores indicate better choices.
[0059] Based on the reservation parking and charging scheduling score, the parking and charging combination with the highest score is selected. This means prioritizing parking spaces and charging piles that can both meet the arrival requirements of the reserved vehicles and efficiently match their parking and charging needs. Based on the determined reserved parking space unit and reserved charging pile unit, a reservation parking and charging facility scheduling plan is generated. This scheduling plan is sent to the reserved vehicles through in-vehicle navigation systems, mobile applications, etc., to help them navigate to the predetermined parking and charging locations and ensure an efficient parking and charging experience.
[0060] Example 2 is based on the same inventive concept as the intelligent scheduling method for parking and charging facilities based on lifecycle management in the previous examples, such as... Figure 2 As shown in the embodiment of this application, an intelligent scheduling system for parking and charging facilities based on lifecycle management is provided. The system includes:
[0061] The parking and charging demand acquisition module 10 is used to record the parking start time when a target vehicle enters the target parking area and interactively acquire the parking and charging demand information of the target vehicle, wherein the parking and charging demand information includes parking duration and charging demand amount; the parking space unit acquisition module 20 is used to acquire M parking space units and N charging pile units in the target parking area, wherein M > N; the life cycle data backtracking module 30 is used to backtrack the M parking space units and N charging pile units based on the parking start time and predetermined life cycle nodes, including the M parking space units and N charging pile units' full life cycle datasets, as well as historical environment data. The system includes a dataset; a health status assessment module 40, used to assess the health status of parking and charging facilities based on the M parking space lifecycle datasets, N charging pile lifecycle datasets, and historical environment datasets, and output the health status characteristics of the M parking spaces and N charging piles; a facility scheduling analysis module 50, used to perform parking and charging facility scheduling analysis based on the M parking space health status characteristics, N charging pile health status characteristics, parking duration, and charging demand, and generate a parking and charging facility scheduling plan; and a parking and charging guidance module 60, used to generate parking and charging guidance information based on the parking and charging facility scheduling plan and send it to the target vehicle.
[0062] Furthermore, the predetermined life cycle nodes are divided according to the life cycle status attributes of the M parking space units and N charging pile units. The predetermined life cycle nodes include construction nodes, commissioning nodes, operation nodes, maintenance nodes, and decommissioning nodes.
[0063] Furthermore, the lifecycle data backtracking module 30 is used to perform the following operation steps:
[0064] For the M parking space units, parking space and supporting data, parking space commissioning initialization data, parking space operation behavior data, and parking space operation and maintenance data are collected from the construction node, commissioning node, operation node, and maintenance node, respectively, and integrated to obtain the M parking space full life cycle dataset. For the N charging pile units, charging pile equipment and electrical configuration data, charging pile commissioning initialization data, charging pile operation behavior data, and charging pile operation and maintenance data are collected from the construction node, commissioning node, operation node, and maintenance node, respectively, and integrated to obtain the N charging pile full life cycle dataset. For any parking space unit and any charging pile unit in the elimination node, an unusable mark is made, and elimination archive data is collected and added to the M parking space full life cycle dataset and the N charging pile full life cycle dataset.
[0065] Furthermore, the health status assessment module 40 is used to perform the following operation steps:
[0066] Lifecycle features are extracted from the M parking space full lifecycle datasets to construct a parking space operation feature set; lifecycle features are extracted from the N charging pile full lifecycle datasets to construct a charging pile operation feature set; environmental impact features are extracted from the historical environment datasets to construct an environmental impact feature set; based on the parking space operation feature set, the charging pile operation feature set, and the environmental impact feature set, a facility health assessment index system is constructed; based on the facility health assessment index system, the health status of the M parking space units and the N charging pile units is calculated to obtain M parking space health status indicators and M charging pile health status indicators; corresponding health status features are extracted from the M parking space health status indicators and the M charging pile health status indicators to generate the M parking space health status features and the N charging pile health status features.
[0067] Furthermore, the facility scheduling and analysis module 50 is used to perform the following operation steps:
[0068] Based on the parking duration and charging demand, candidate parking space units and candidate charging pile units that meet the parking duration and charging capacity constraints are selected from the M parking space units and N charging pile units. Based on these candidate sets, a parking-charging combination set is constructed, and a parking-charging matching relationship matrix is established according to the spatial proximity, binding, or service radius relationship between parking spaces and charging piles. For each parking-charging combination in the matching relationship matrix, a facility health score is calculated based on the corresponding parking space health status characteristics and charging pile health status characteristics, and a service matching score is calculated based on the parking duration and charging demand. The facility health score and service matching score are weighted and fused to generate a scheduling priority score for each parking-charging combination. The target parking space unit and target charging pile unit are located based on the scheduling priority score to generate the parking-charging facility scheduling scheme.
[0069] Furthermore, the facility scheduling and analysis module 50 is used to perform the following operation steps:
[0070] Obtain real-time resource occupancy information and queuing information for the target parking area, calculate resource availability scores for each parking and charging combination, and adjust the scheduling priority scores accordingly.
[0071] Furthermore, the system also includes a parking and charging reservation module for performing the following operations:
[0072] Upon receiving a parking and charging reservation request, the system connects to the digital transportation platform to obtain real-time traffic data, including real-time traffic flow, road congestion index, vehicle speed, and road event information around the target parking area. Based on the real-time traffic data, the system calculates the estimated travel time for the reserved vehicle to reach each parking and charging combination, generating an arrival efficiency score. It then obtains the reservation scheduling priority score for the reserved vehicle. The system merges the arrival efficiency score and the reservation scheduling priority score to obtain a parking and charging reservation scheduling score. Finally, based on the parking and charging reservation scheduling score, the system determines the reserved parking space unit and the reserved charging pile unit, generating a parking and charging reservation facility scheduling plan.
[0073] Through the foregoing detailed description of the intelligent scheduling method for parking and charging facilities based on lifecycle management, those skilled in the art can clearly understand the intelligent scheduling system for parking and charging facilities based on lifecycle management in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to in the method section.
[0074] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.
Claims
1. A method for intelligent scheduling of parking and charging facilities based on lifecycle management, characterized in that, The method includes: When the target vehicle enters the target parking area, the parking start time is recorded, and the parking and charging demand information of the target vehicle is obtained interactively. The parking and charging demand information includes the parking duration and the charging demand amount. Obtain M parking space units and N charging pile units in the target parking area, where M > N; Starting from the parking start time, based on predetermined lifecycle nodes, backtrack the M parking space units and N charging pile units to obtain the full lifecycle datasets of the M parking spaces and N charging piles, as well as the historical environment dataset. Based on the M parking space full life cycle datasets, N charging pile full life cycle datasets, and historical environment datasets, a health status assessment of parking and charging facilities is conducted, and the health status characteristics of M parking spaces and N charging piles are output. Based on the health status characteristics of the M parking spaces, the health status characteristics of the N charging piles, and the parking duration and charging demand, a parking and charging facility scheduling analysis is performed to generate a parking and charging facility scheduling plan. Parking and charging guidance information is generated based on the parking and charging facility scheduling plan and sent to the target vehicle.
2. The intelligent scheduling method for parking and charging facilities based on lifecycle management as described in claim 1, characterized in that, The predetermined life cycle nodes are divided according to the life cycle status attributes of the M parking space units and N charging pile units. The predetermined life cycle nodes include construction nodes, commissioning nodes, operation nodes, maintenance nodes, and decommissioning nodes.
3. The intelligent scheduling method for parking and charging facilities based on lifecycle management as described in claim 2, characterized in that, include: For the M parking space units, parking space and supporting data, parking space initialization data, parking space operation behavior data, and parking space operation and maintenance data are collected from the construction node, commissioning node, operation node, and maintenance node respectively, and integrated to obtain the full life cycle dataset of the M parking spaces; For the N charging pile units, charging pile equipment and electrical configuration data, charging pile commissioning initialization data, charging pile operation behavior data, and charging pile operation and maintenance data are collected from the construction node, commissioning node, operation node, and maintenance node respectively, and integrated to obtain the full life cycle dataset of the N charging piles; For any parking space unit or any charging pile unit that is in the elimination node, an unusable mark is made, and elimination archive data is collected and added to the M parking space full life cycle datasets and N charging pile full life cycle datasets.
4. The intelligent scheduling method for parking and charging facilities based on lifecycle management as described in claim 1, characterized in that, Conduct a health status assessment of parking and charging facilities, including: Lifecycle features are extracted from the full lifecycle datasets of the M parking spaces to construct a parking space operation feature set; Lifecycle features are extracted from the N full lifecycle datasets of the charging piles to construct a charging pile operation feature set; Environmental impact features are extracted from the historical environmental dataset to construct an environmental impact feature set; Based on the aforementioned set of parking space operation characteristics, set of charging pile operation characteristics, and set of environmental impact characteristics, a facility health assessment index system is constructed. Based on the facility health assessment index system, the health status of the M parking space units and N charging pile units is calculated to obtain the health status index of the M parking spaces and the health status index of the M charging piles. Based on the health indicators of the M parking spaces and the M charging piles, extract the corresponding health status features to generate the health status features of the M parking spaces and the health status features of the N charging piles.
5. The intelligent scheduling method for parking and charging facilities based on lifecycle management as described in claim 1, characterized in that, Perform parking and charging facility scheduling analysis to generate a parking and charging facility scheduling plan, including: Based on the parking duration and charging demand, a set of candidate parking space units and a set of candidate charging pile units that meet the parking duration constraint and charging capacity constraint are selected from the M parking space units and N charging pile units. Based on the candidate parking space unit set and the candidate charging pile unit set, a parking and charging combination set is constructed, and a parking and charging matching relationship matrix is established according to the spatial proximity relationship, binding relationship or service radius relationship between parking spaces and charging piles. For each parking and charging combination in the parking and charging matching matrix, a facility health score is calculated by combining the corresponding parking space health status characteristics and charging pile health status characteristics, and a service matching score is calculated based on the parking duration and charging demand. The facility health score and service matching score are weighted and fused to generate a scheduling priority score for each parking and charging combination; Based on the scheduling priority score, the target parking space unit and the target charging pile unit are located, and the parking and charging facility scheduling scheme is generated.
6. The intelligent scheduling method for parking and charging facilities based on lifecycle management as described in claim 5, characterized in that, Also includes: Obtain real-time resource occupancy and queuing information for the target parking area, and calculate resource availability scores for each parking and charging combination; The scheduling priority score is adjusted and compensated based on the resource availability score.
7. The intelligent scheduling method for parking and charging facilities based on lifecycle management as described in claim 1, characterized in that, Also includes: When a parking and charging reservation is received, the system connects to the digital transportation platform to obtain real-time traffic operation data, which includes real-time traffic flow, road congestion index, vehicle speed and road event information of the roads surrounding the target parking area. Based on the real-time traffic operation data, the estimated travel time for the reserved vehicle to arrive at each parking and charging combination is calculated, and an arrival efficiency score is generated. Obtain the reservation scheduling priority score of the reserved vehicle; The arrival efficiency score and the reservation scheduling priority score are fused together to obtain the reservation parking and charging scheduling score; Based on the reservation parking and charging scheduling score, the reservation parking space unit and the reservation charging pile unit are determined, and a reservation parking and charging facility scheduling plan is generated.
8. A smart scheduling system for parking and charging facilities based on lifecycle management, characterized in that, The system is used to implement the intelligent scheduling method for parking and charging facilities based on lifecycle management as described in any one of claims 1-7, the system comprising: The parking and charging demand acquisition module is used to record the parking start time when the target vehicle enters the target parking area and interactively acquire the parking and charging demand information of the target vehicle, wherein the parking and charging demand information includes parking duration and charging demand amount. The parking space unit acquisition module is used to acquire M parking space units and N charging pile units in the target parking area, where M > N; The lifecycle data backtracking module is used to backtrack the M parking space units and N charging pile units' full lifecycle datasets and N charging pile full lifecycle datasets, as well as historical environment datasets, based on the parking start time and predetermined lifecycle nodes. The health status assessment module is used to assess the health status of parking and charging facilities based on the M parking space full life cycle datasets, N charging pile full life cycle datasets, and historical environmental datasets, and output the health status characteristics of the M parking spaces and the N charging piles. The facility scheduling and analysis module is used to perform parking and charging facility scheduling analysis based on the health status characteristics of the M parking spaces, the health status characteristics of the N charging piles, as well as the parking duration and charging demand, and generate a parking and charging facility scheduling plan. The parking and charging guidance module is used to generate parking and charging guidance information according to the parking and charging facility scheduling plan and send it to the target vehicle.