Sanitation vehicle management method, device, equipment and storage medium

Abstract

The present application provides a sanitation vehicle management method, device, equipment and storage medium, which relates to the technical field of construction vehicle scheduling. The method includes: obtaining environmental data of multiple areas to be cleaned in a target area, and calculating the cleanliness parameters of multiple areas to be cleaned according to the environmental data; determining the target cleaning area whose cleanliness parameters are lower than the preset parameters among the multiple areas to be cleaned, and the amount of garbage to be cleaned in the target cleaning area; obtaining the positions, remaining loads and remaining power of multiple sanitation vehicles in the target area; determining the initial operation plan of each sanitation vehicle according to the position of each sanitation vehicle; based on the amount of garbage to be cleaned in the target cleaning area, combined with the remaining loads and remaining power of each sanitation vehicle, adjusting the initial operation plan of each sanitation vehicle to obtain the target operation plan of each sanitation vehicle. The technical effect of the present application is: used to improve the operation quality of sanitation vehicles.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle dispatching, and in particular to a method, device, equipment and storage medium for managing sanitation vehicles. Background Art

[0002] Sanitation vehicles are one of the most important tools for urban cleaning, and they play a key role in maintaining urban environmental hygiene. However, as cities expand in size and the amount of garbage generated increases, how to effectively dispatch and manage these sanitation vehicles has become a complex task.

[0003] In the prior art, a pre-set operation plan is generally used to arrange the cleaning operations of sanitation vehicles according to fixed routes and times. Although this method is simple and easy to implement, it lacks flexibility and pertinence. Under this model, the formulation and execution of the sanitation vehicle operation plan lacks sufficient data support and real-time dynamic optimization, making it difficult to fully tap the efficiency of sanitation vehicle operations, resulting in reduced operation quality of sanitation vehicles. Summary of the invention

[0004] The present application provides a sanitation vehicle management method for improving the operation quality of sanitation vehicles.

[0005] In the first aspect, the present application provides a sanitation vehicle management method, the method comprising: obtaining environmental data of multiple areas to be cleaned in a target area, and calculating the cleanliness parameters of the multiple areas to be cleaned based on the environmental data; determining a target cleaning area where the cleanliness parameters of the multiple areas to be cleaned are lower than preset parameters, and the amount of garbage to be cleaned in the target cleaning area; obtaining the positions, remaining load capacities, and remaining power of multiple sanitation vehicles in the target area; determining an initial operation plan of each sanitation vehicle based on the positions of each sanitation vehicle; and adjusting the initial operation plan of each sanitation vehicle on the basis of the amount of garbage to be cleaned in the target cleaning area and in combination with the remaining load capacities and remaining power of each sanitation vehicle to obtain a target operation plan for each sanitation vehicle.

[0006] By adopting the above technical scheme, the sanitation vehicle management method realizes accurate assessment of cleaning needs by obtaining environmental data of multiple areas to be cleaned in the target area and calculating cleaning parameters. By determining the target cleaning area and the amount of garbage to be cleaned whose cleaning parameters are lower than the preset parameters, the method can accurately identify the areas that need to be cleaned, avoiding the problems of resource waste and insufficient cleaning. At the same time, by obtaining the location, remaining load and remaining power of the sanitation vehicle, the method fully grasps the real-time status of vehicle resources. Based on these data, the method first determines the initial operation plan according to the location of the sanitation vehicle, and then adjusts it in combination with the amount of garbage to be cleaned in the target cleaning area, the remaining load and the remaining power of the vehicle, and finally obtains the optimized target operation plan. By comprehensively considering environmental data, vehicle status and cleaning needs, the method realizes intelligent management of sanitation vehicles, improves overall cleaning efficiency, reduces unnecessary operations, and improves the operation quality of sanitation vehicles.

[0007] Optionally, the calculating the cleanliness parameters of the multiple areas to be cleaned according to the environmental data, wherein the environmental data includes the type of garbage and the area covered by garbage, comprises: substituting the type of garbage and the area covered by garbage into a preset formula to calculate the cleanliness parameters of the multiple areas to be cleaned; wherein, Wherein, P is the cleanliness parameter of each area to be cleaned, K is the preset parameter, C i is the cleaning difficulty coefficient of the i-th type of garbage, A i is the garbage coverage area of ​​the i-th type of garbage, S i is the garbage impact parameter corresponding to the i-th type of garbage.

[0008] By adopting the above technical solution and taking into account the characteristics of different types of garbage, the method can more accurately identify and prioritize garbage areas that are difficult to clean, cover a wide area, or have a significant environmental impact, thereby improving the pertinence and efficiency of cleaning work. This clean parameter calculation method based on multi-dimensional data not only improves the accuracy of sanitation vehicle scheduling, but also allocates cleaning resources more reasonably, avoiding the problems of resource waste and insufficient cleaning. At the same time, the flexibility of this method allows managers to adjust preset parameters according to actual needs to adapt to the cleaning standards of different cities or regions. Overall, this improved clean parameter calculation method provides a more scientific and accurate decision-making basis for sanitation vehicle management, helps to improve overall cleaning efficiency, optimize resource allocation, and thus improve the quality and effectiveness of urban environmental management.

[0009] Optionally, determining an initial operation plan for each sanitation vehicle based on the position of each sanitation vehicle includes: obtaining road network information within the target area, and calculating the distance from each sanitation vehicle to the target cleaning area based on the position of each sanitation vehicle in combination with the road network information; determining a route for each sanitation vehicle to travel to the target cleaning area based on the distance from each sanitation vehicle to the target cleaning area, and using the route for each sanitation vehicle to travel to the target cleaning area as the initial operation plan for each sanitation vehicle.

[0010] By adopting the above technical solution, the road network information in the target area is obtained, which provides basic data support for subsequent route planning. Combined with the real-time location and road network information of the sanitation vehicles, the distance from each sanitation vehicle to the target cleaning area can be accurately calculated. This distance calculation method based on actual road conditions is more in line with the actual situation than the simple straight-line distance calculation, and can more accurately reflect the actual distance traveled by the vehicle. Through the calculated distance data, the method can determine the optimal driving route for each sanitation vehicle and use these routes as the initial operation plan. This route planning not only takes into account the distance factor, but also implicitly includes the influence of road conditions, traffic flow, etc., which can help the vehicle choose the most efficient driving path. This way of formulating the initial operation plan can significantly reduce the invalid driving time and distance of sanitation vehicles and improve the efficiency of vehicle scheduling. At the same time, by optimizing the driving route, the fuel consumption and maintenance cost of the vehicle can be reduced, and environmental pollution can be reduced. In addition, this planning method based on real-time location and road network also improves the responsiveness of the sanitation system to emergencies, and can quickly adjust the vehicle route to meet emergency cleaning needs.

[0011] Optionally, based on the amount of garbage to be cleaned in the target cleaning area, combined with the remaining load capacity and the remaining power of each sanitation vehicle, the initial operation plan of each sanitation vehicle is adjusted to obtain a target operation plan for each sanitation vehicle, including: calculating the final remaining load capacity and the final remaining power of each sanitation vehicle after completing the initial operation plan, as well as the remaining amount of garbage to be cleaned in the target cleaning area; combining the final remaining load capacity, the final remaining power and the remaining amount of garbage to be cleaned in the target cleaning area, the initial operation plan of each sanitation vehicle is adjusted to obtain a target operation plan for each sanitation vehicle.

[0012] By adopting the above technical solution, the final remaining load and final remaining power of each sanitation vehicle after completing the initial operation plan, as well as the remaining amount of garbage to be cleaned in the target cleaning area, are calculated. This forward-looking calculation provides an accurate data basis for subsequent plan adjustments. By comprehensively considering the final remaining load of the vehicle, the final remaining power and the actual cleaning needs of the target cleaning area, the method can make more detailed and reasonable adjustments to the initial operation plan, thereby obtaining an optimized target operation plan. This dynamic adjustment mechanism can effectively solve problems that may exist in the initial plan, such as the fact that the load of some vehicles is insufficient to complete the assigned tasks, or the power is insufficient to support the entire operation. Through timely adjustments, the method can better balance the workload of each sanitation vehicle and avoid the situation where some vehicle resources are idle while other vehicles are overloaded. At the same time, this adjustment also takes into account the changes in the actual cleaning needs of the target cleaning area to ensure that the cleaning task can be fully completed.

[0013] Optionally, the initial operation plan of each sanitation vehicle is adjusted in combination with the final remaining load, the final remaining power and the remaining amount of garbage to be cleaned in the target cleaning area to obtain a target operation plan for each sanitation vehicle, including: determining a first sanitation vehicle with additional operation capacity according to the final remaining load and the final remaining power of each sanitation vehicle, and calculating the maximum additional operation mileage and the maximum additional operation volume that the first sanitation vehicle can perform; determining the additional operation plan of the first sanitation vehicle in combination with the final position of the first sanitation vehicle after completing the initial operation plan, the maximum additional operation mileage and the maximum additional operation volume that the first sanitation vehicle can perform, the position of the target sub-area in the target cleaning area where the remaining amount of garbage to be cleaned exists, and the remaining amount of garbage to be cleaned in the target sub-area; using the additional operation plan of the first sanitation vehicle and the initial operation plan as the target operation plan of the first sanitation vehicle; using the initial operation plan of the remaining sanitation vehicles as the target operation plan of the remaining sanitation vehicles.

[0014] By adopting the above technical solution, the first sanitation vehicle with additional operating capacity is identified according to the final remaining load and the final remaining power of each sanitation vehicle, and the maximum additional operating mileage and the maximum additional operating volume that can be performed are accurately calculated. This meticulous evaluation ensures the feasibility and rationality of the additional task allocation. Subsequently, the method comprehensively considers the final position of the first sanitation vehicle after completing the initial operation plan, its maximum additional operating capacity that can be performed, the position of the target sub-area with the remaining amount of garbage to be cleaned in the target cleaning area, and the remaining amount of garbage to be cleaned, so as to formulate the optimal additional operation plan. This multi-dimensional consideration ensures that the additional operation plan not only makes full use of the remaining capacity of the vehicle, but also maximizes the remaining cleaning needs. By combining the additional operation plan with the initial operation plan, the method formulates a more comprehensive and efficient target operation plan for the first sanitation vehicle. At the same time, for the remaining sanitation vehicles that do not have additional operating capacity, the method retains their initial operation plan as the target operation plan, avoiding unnecessary adjustments and possible waste of resources. This differentiated plan adjustment strategy not only improves the overall cleaning efficiency, but also maximizes the utilization of sanitation vehicle resources.

[0015] Optionally, after adjusting the initial operation plan of each of the sanitation vehicles to obtain the target operation plan of each of the sanitation vehicles, the method further includes: obtaining weather conditions and road traffic conditions in the target area; optimizing and adjusting the target operation plan of each of the sanitation vehicles according to the weather conditions and road traffic in the target area to obtain an optimized target operation plan for each of the sanitation vehicles; sending the optimized target operation plan of each of the sanitation vehicles to the corresponding sanitation vehicle, and controlling each of the sanitation vehicles to perform cleaning operations according to the optimized target operation plan.

[0016] By adopting the above technical solution, after completing the preliminary target operation plan, the weather conditions and road traffic conditions in the target area are also obtained. These real-time environmental data provide a key basis for the optimization and adjustment of the operation plan. By comprehensively considering weather and traffic factors, the method can make more detailed and practical optimization and adjustment of the target operation plan of each sanitation vehicle, thereby obtaining a more feasible optimized target operation plan. This optimization and adjustment mechanism based on real-time environmental factors greatly improves the execution efficiency and reliability of the operation plan.

[0017] Optionally, after adjusting the initial operation plan of each of the sanitation vehicles to obtain the target operation plan of each of the sanitation vehicles, the method further includes: sending the target operation plan of each of the sanitation vehicles to the corresponding sanitation vehicle to control each of the sanitation vehicles to perform the cleaning operation according to its target operation plan; obtaining the cleaning operation execution progress information of each of the sanitation vehicles, and judging whether there is a second sanitation vehicle with abnormal operation progress based on the cleaning operation execution progress information; if there is a second sanitation vehicle with abnormal operation progress, determining the cause of the abnormal operation of the second sanitation vehicle, and adjusting the target operation plan of the second sanitation vehicle based on the cause of the abnormal operation to obtain an updated target operation plan of the second sanitation vehicle; and sending the updated target operation plan to the second sanitation vehicle so that the second sanitation vehicle performs the cleaning operation according to the updated target operation plan.

[0018] By adopting the above technical solution, the target operation plan of each sanitation vehicle is sent to the corresponding vehicle, realizing a rapid transformation from decision-making to execution. By obtaining the cleaning operation execution progress information of each sanitation vehicle in real time, the method establishes a continuous feedback monitoring system, enabling managers to grasp the operation status in a timely manner. This real-time monitoring mechanism provides a basis for quickly identifying and responding to abnormal operations. When the system determines that there is a second sanitation vehicle with abnormal operation progress, the method can quickly determine the cause of the abnormal operation, and make targeted adjustments to the target operation plan of the second sanitation vehicle according to the specific cause to obtain an updated target operation plan. This dynamic adjustment strategy based on real-time feedback greatly improves the system's ability to respond to emergencies and ensures the continuity and efficiency of cleaning operations. By sending the updated target operation plan to the second sanitation vehicle in a timely manner, the method realizes the rapid resolution of problems and the seamless connection of operations, minimizing the waste of time and resources caused by abnormal situations. This closed-loop management method not only improves the operating efficiency of a single sanitation vehicle, but also optimizes the resource allocation and coordination capabilities of the entire cleaning system.

[0019] In the second aspect, the present application provides a sanitation vehicle management device, which includes: a first acquisition module, a first determination module, a second acquisition module, a second determination module and an output module; wherein the first acquisition module is used to acquire environmental data of multiple areas to be cleaned in a target area, and calculate the cleanliness parameters of the multiple areas to be cleaned based on the environmental data; the first determination module is used to determine the target cleaning area where the cleanliness parameters of the multiple areas to be cleaned are lower than the preset parameters, and the amount of garbage to be cleaned in the target cleaning area; the second acquisition module is used to acquire the positions, remaining loads and remaining power of multiple sanitation vehicles in the target area; the second determination module is used to determine the initial operation plan of each of the sanitation vehicles based on the positions of each of the sanitation vehicles; the output module is used to adjust the initial operation plan of each of the sanitation vehicles based on the amount of garbage to be cleaned in the target cleaning area, combined with the remaining load and the remaining power of each of the sanitation vehicles, to obtain the target operation plan of each of the sanitation vehicles.

[0020] In the third aspect, the present application provides an electronic device that adopts the following technical solution: it includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a computer program such as any of the above-mentioned sanitation vehicle management methods.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: storing a computer program that can be loaded by a processor and execute any of the above-mentioned sanitation vehicle management methods.

[0022] In summary, the present application includes at least one of the following beneficial technical effects:

[0023] 1. By acquiring environmental data of multiple areas to be cleaned in the target area and calculating the cleaning parameters, an accurate assessment of cleaning needs is achieved. By determining the target cleaning areas and the amount of garbage to be cleaned whose cleaning parameters are lower than the preset parameters, the method can accurately identify areas that urgently need cleaning, avoiding the problems of resource waste and insufficient cleaning. At the same time, by acquiring the location, remaining load, and remaining power of the sanitation vehicle, the method fully grasps the real-time status of vehicle resources. Based on these data, the method first determines the initial operation plan according to the location of the sanitation vehicle, and then adjusts it in combination with the amount of garbage to be cleaned in the target cleaning area, the remaining load, and the remaining power of the vehicle, and finally obtains the optimized target operation plan;

[0024] 2. By comprehensively considering environmental data, vehicle status and cleaning needs, intelligent management of sanitation vehicles is achieved, the overall cleaning efficiency is improved, unnecessary operations are reduced, and the operation quality of sanitation vehicles is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of a sanitation vehicle management method provided in an embodiment of the present application;

[0026] Figure 2 It is a structural schematic diagram of a sanitation vehicle management device provided in an embodiment of the present application;

[0027] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0028] Description of reference numerals: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0030] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0031] Figure 1 Schematic diagram of a sanitation vehicle management method provided in an embodiment of the present application. Figure 1 As shown, the method includes S101-S105:

[0032] S101, obtaining environmental data of multiple areas to be cleaned in a target area, and calculating cleaning parameters of the multiple areas to be cleaned according to the environmental data.

[0033] In one example, environmental data can include the type of garbage and the area covered by the garbage. First, environmental data is obtained using sensors and cameras installed on sanitation vehicles. These devices can capture information such as the type of garbage and the area covered in real time. Sensors can include image sensors, LIDAR, etc. to help identify different types of garbage.

[0034] Smart monitoring devices can also be deployed at fixed locations within the target area. These devices can continuously monitor the environmental conditions in a specific area and transmit data to a central system for analysis. During the data collection process, image recognition algorithms are used to classify the types of garbage and calculate their coverage and distribution.

[0035] In addition, combined with the Internet of Things technology, the collected data is transmitted to the cloud platform through wireless communication for centralized processing. The cloud platform uses advanced data analysis and machine learning algorithms to update and analyze environmental data in real time to ensure the accuracy and reliability of the data. In this way, the system can comprehensively and accurately obtain environmental data in the target area, providing a reliable basis for calculating clean parameters and subsequent cleaning operation plans.

[0036] After obtaining the environmental data, the preset calculation formula is used to calculate the cleanliness parameters of each area to be cleaned. Specifically, the calculation formula for the cleanliness parameters is: Where P is the cleanliness parameter of each area to be cleaned, K is the preset parameter, and C i is the cleaning difficulty coefficient of the i-th type of garbage, A i is the garbage coverage area of ​​the i-th type of garbage, S i is the garbage impact parameter corresponding to the i-th type of garbage.

[0037] The formula takes into account the impact factors of different types of garbage in a weighted manner. Each type of garbage has different cleaning difficulty and impact on the environment, so different weight coefficients C are required for each type of garbage. i and S i , to ensure the accuracy of the calculation. i It reflects the distribution range of garbage. The larger the coverage area, the more cleaning work is needed in the area. By accumulating n types of garbage, the formula combines the impact of all types of garbage on the cleanliness of the area, rather than a single factor, to ensure comprehensive consideration. K provides the ability to adjust the results of the entire formula to adapt to the specific policies and standards of different cities or regions. The reason for this setting is to fully consider the diversity and complexity of garbage when evaluating cleaning needs, and to ensure the rational allocation and efficient use of sanitation resources.

[0038] S102, determining a target cleaning area whose cleaning parameter is lower than a preset parameter among the multiple areas to be cleaned, and the amount of garbage to be cleaned in the target cleaning area.

[0039] In one example, during the implementation process, the cleanliness parameters calculated in step S101 are first compared with the cleanliness standard parameters preset by the system. The preset parameters are thresholds set according to the city's cleanliness standards and environmental requirements, and are used to judge the urgency of the cleaning needs. When the cleanliness parameters of a certain area to be cleaned are lower than the preset parameters, the system will mark it as a target cleaning area.

[0040] Next, the system needs to evaluate the amount of garbage to be cleaned in these target cleaning areas. By combining the type of garbage, coverage area and other relevant information in the environmental data, the amount of garbage in each target area is calculated. This evaluation process can be automatically completed through data analysis and image recognition technology to ensure the accuracy and efficiency of the results.

[0041] S103, obtaining the positions, remaining loads, and remaining power of multiple sanitation vehicles in the target area.

[0042] In one example, during the implementation process, the location information of each sanitation vehicle is first obtained in real time through the GPS device on the vehicle. This information ensures that the current location of each vehicle can be accurately understood, providing support for subsequent route planning and scheduling.

[0043] Next, the remaining load of each sanitation vehicle is obtained. This can be monitored by on-board sensors, which can provide real-time feedback on the current load status of the vehicle so as to reasonably allocate cleaning tasks and prevent overloading or waste of resources.

[0044] At the same time, it is also necessary to obtain the vehicle's remaining power information. This data is especially important for electric vehicles, because the power directly affects the vehicle's endurance and operating range. The on-board power monitoring system can accurately evaluate the endurance status of each vehicle.

[0045] S104, determining an initial operation plan for each sanitation vehicle according to the position of each sanitation vehicle.

[0046] In one example, the vehicle location information obtained from step S103 is first used in combination with the city's road network information to calculate the shortest path for each vehicle to reach each target cleaning area through a path planning algorithm. Next, the initial operation plan for each sanitation vehicle is determined based on the calculated route. This plan includes the vehicle's route, the scheduled cleaning area, and the estimated arrival time. The system will prioritize tasks that are close in distance and have appropriate vehicle loads to maximize efficiency and reduce unnecessary mileage.

[0047] Based on the above embodiment, as an optional implementation, in S104, determining the initial operation plan of each sanitation vehicle according to the position of each sanitation vehicle specifically includes S401-S402:

[0048] S401, obtaining road network information in the target area, and calculating the distance of each sanitation vehicle to the target cleaning area according to the position of each sanitation vehicle and the road network information.

[0049] In one example, the road network information in the target area needs to be obtained first. The purpose of this step is to accurately reflect the actual situation of urban roads, including key data such as road type, length, and traffic conditions. Road network information can be obtained by accessing the database of the urban traffic management system or using electronic map data provided by the geographic information system (GIS). These data not only contain static road layout information, but may also include dynamic information such as real-time traffic flow and road construction, providing a comprehensive and accurate basis for subsequent path planning.

[0050] After obtaining the road network information, combined with the real-time location data of each sanitation vehicle obtained in step S103, the path planning algorithm is used to calculate the optimal path and corresponding distance for each sanitation vehicle to reach the target cleaning area. In the calculation process, not only the physical distance of the road is considered, but also factors such as road type and current traffic conditions are taken into consideration to more accurately estimate the actual driving distance and time.

[0051] For example, for a sanitation vehicle A located in the city center, consider multiple possible paths from its current location to the nearest target cleaning area X. By analyzing the road network information, the system may find that the path with the shortest straight-line distance is not suitable for selection due to traffic congestion, and instead choose an alternative route that is slightly longer but has smoother traffic, thereby obtaining a more reasonable distance estimate and travel time prediction.

[0052] According to the distance of each sanitation vehicle to the target cleaning area, the route of each sanitation vehicle to the target cleaning area is determined, and the route of each sanitation vehicle to the target cleaning area is used as the initial operation plan of each sanitation vehicle.

[0053] In one example, advanced path planning algorithms are first used to combine real-time traffic data and historical traffic patterns to calculate multiple possible routes for each sanitation vehicle. These routes are not only the shortest routes, but also take into account factors such as road conditions, estimated driving time, and energy consumption. For example, for sanitation vehicle A, the system may generate three alternative routes: Route 1 is the shortest but may pass through traffic congestion areas, Route 2 is longer but has smooth traffic, and Route 3 balances distance and traffic conditions. The system will conduct a comprehensive evaluation of these routes and select the best one as the initial operation plan for the vehicle.

[0054] During the route selection process, the system will also consider the special needs of sanitation vehicles. For example, for large sanitation vehicles, the system will give priority to wide main roads and avoid narrow streets and alleys; for electric sanitation vehicles, the system will consider the distribution of charging stations along the route to ensure that the vehicle can be recharged in time when needed. In addition, the system will also take into account the remaining load and remaining power of each vehicle (such as the information obtained in step S103) to ensure that the selected route can match the current status and operating capacity of the vehicle.

[0055] After determining the optimal routes, the system will use these routes as the initial operation plan for each sanitation vehicle. This initial operation plan not only includes the detailed driving route, but also includes information such as the estimated arrival time and key nodes along the way. For example, the initial operation plan for sanitation vehicle B may include: starting from the current location, passing through Road A and Road B to reach the target cleaning area Y, with an estimated driving time of 45 minutes, and passing through two areas with dense traffic lights on the way.

[0056] S105, based on the amount of garbage to be cleaned in the target cleaning area, combined with the remaining load capacity and remaining power of each sanitation vehicle, the initial operation plan of each sanitation vehicle is adjusted to obtain a target operation plan of each sanitation vehicle.

[0057] In one example, during implementation, the amount of garbage to be cleaned in each target cleaning area is evaluated. This data comes from the previously calculated clean parameters to ensure that the amount of garbage in each area is accurately evaluated. Next, the remaining load and remaining power information of each sanitation vehicle is obtained. This information is crucial because it directly affects the amount of tasks that the vehicle can undertake and its endurance.

[0058] On this basis, the initial operation plan of each sanitation vehicle is adjusted. During the adjustment process, the system will give priority to assigning vehicles with sufficient load and power to clean up areas with large amounts of garbage to avoid vehicle overload or running out of power midway, ensuring that the adjusted plan can maximize cleaning efficiency and reduce vehicle idle time.

[0059] Based on the above embodiment, as an optional implementation, in S105, based on the amount of garbage to be cleaned in the target cleaning area, combined with the remaining load and remaining power of each sanitation vehicle, the initial operation plan of each sanitation vehicle is adjusted to obtain the target operation plan of each sanitation vehicle, which specifically includes S501-S502:

[0060] S501, calculating the final remaining load and final remaining power of each sanitation vehicle after completing the initial operation plan, and the remaining amount of garbage to be cleaned in the target cleaning area.

[0061] In one example, the system first performs a series of prediction calculations based on the initial remaining load and initial remaining power of each sanitation vehicle obtained in step S103, combined with the amount of garbage to be cleaned in the target cleaning area determined in step S102, and the travel distance calculated in step S401. This calculation process needs to consider multiple factors, including the vehicle's loading capacity, cleaning efficiency, energy consumption rate, etc.

[0062] For example, for sanitation vehicle A, the system predicts the final remaining load based on its initial remaining load (e.g., 10 cubic meters) and the amount of garbage to be cleaned in the target cleaning area X (e.g., 8 cubic meters). At the same time, considering the possible compression rate during the cleaning process, the system may apply a compression factor (e.g., 1.2) to more accurately estimate the final remaining load. Therefore, the final remaining load of sanitation vehicle A may be calculated as: 10-(8 / 1.2) = 3.33 cubic meters.

[0063] For the calculation of the final remaining power, the system will consider the initial remaining power of the vehicle (e.g. 80%), the expected driving distance (e.g. 20 km), the expected power consumption of the cleaning operation, and the energy efficiency of the vehicle. Assuming that the vehicle consumes an average of 1% of power per kilometer, the cleaning operation consumes 5% of power per hour, and the expected operation time is 2 hours, the final remaining power of sanitation vehicle A may be calculated as: 80%-(20*1%)-(2*5%)=50%.

[0064] At the same time, the system also needs to calculate the remaining amount of garbage to be cleaned in the target cleaning area. This calculation is based on the initial amount of garbage to be cleaned and the cleaning capacity of the sanitation vehicle. If sanitation vehicle A can completely clean the garbage in the target cleaning area X, then the remaining amount of garbage to be cleaned will be 0. However, if the loading capacity of the vehicle is not enough for complete cleaning, the system will calculate the remaining amount of garbage to provide a basis for subsequent cleaning plans.

[0065] S502, adjusting the initial operation plan of each sanitation vehicle based on the final remaining load, the final remaining power and the remaining amount of garbage to be cleaned in the target cleaning area of ​​each sanitation vehicle to obtain a target operation plan of each sanitation vehicle.

[0066] In one example, the system first analyzes the calculation result of step S501. For example, for sanitation vehicle A, if its predicted final remaining load is large (such as 3.33 cubic meters), and the remaining amount of garbage to be cleaned in the target cleaning area X is 0, the system may consider assigning additional cleaning tasks to the vehicle. On the contrary, if the final remaining load of vehicle A is close to saturation, the system needs to consider arranging mid-way unloading or dispatching other vehicles to assist.

[0067] Similarly, for the final remaining power, if the forecast shows that the power of vehicle A may drop to a lower level (such as 50%), the system will arrange the appropriate charging time and location in the target operation plan to ensure that the vehicle can complete the entire cleaning task. If multiple vehicles need to be charged at the same time, the system will also consider the capacity of the charging station and arrange the charging sequence and time reasonably to avoid charging congestion.

[0068] During the adjustment process, the system also needs to consider the remaining amount of garbage to be cleaned in the target cleaning area. If the amount of remaining garbage in a certain area exceeds the processing capacity of a single vehicle, the system will consider dispatching multiple vehicles to work together, or breaking down the cleaning task of the area into multiple stages. For example, if the remaining amount of garbage to be cleaned in the target cleaning area Y is 15 cubic meters, which exceeds the loading capacity of sanitation vehicle B (10 cubic meters), the system may arrange vehicle B to clean 10 cubic meters first, and then dispatch nearby vehicle C to complete the remaining 5 cubic meters of cleaning.

[0069] In addition, the system will also take time factors into account when adjusting the job plan. For example, if some cleaning tasks in the initial plan are scheduled during peak traffic hours, the system may adjust the order of tasks and postpone them to a period with smoother traffic to improve cleaning efficiency and reduce the impact on traffic.

[0070] Through this comprehensive consideration and dynamic adjustment, the system will eventually generate an optimized target operation plan for each sanitation vehicle. This plan not only includes detailed cleaning routes and schedules, but also includes necessary unloading and charging arrangements, as well as possible collaborative tasks. For example, the target operation plan of vehicle A may become: first complete the cleaning work of target cleaning area X, then go to the nearby area Y to assist in cleaning the remaining garbage, and perform a 30-minute fast charge at a designated charging station on the way.

[0071] Based on the above embodiment, as an optional implementation, in S502, the initial operation plan of each sanitation vehicle is adjusted in combination with the final remaining load, the final remaining power and the remaining amount of garbage to be cleaned in the target cleaning area of ​​each sanitation vehicle, and the target operation plan of each sanitation vehicle is obtained, which specifically includes S601-S604:

[0072] S601, determining a first sanitation vehicle with additional operating capacity according to the final remaining load and final remaining power of each sanitation vehicle, and calculating the maximum additional operating mileage and maximum additional operating volume that the first sanitation vehicle can perform.

[0073] In one example, the system first analyzes the final remaining load and final remaining power of each sanitation vehicle calculated in step S501. The system sets a threshold, for example, a vehicle with a remaining load greater than 30% of the total load and a remaining power greater than 40% is identified as the first sanitation vehicle with additional operating capacity. The setting of this threshold needs to take into account actual operational requirements and safety margins.

[0074] For example, if the total load of sanitation vehicle A is 10 cubic meters, the total power is 100%, and its final remaining load is 4 cubic meters (40%), and the final remaining power is 50%, then vehicle A may be identified as the first sanitation vehicle with additional operating capacity. The system will make similar judgments for all sanitation vehicles, thereby determining all first sanitation vehicles.

[0075] Next, the system needs to calculate the maximum additional operating mileage and maximum additional operating volume that each No. 1 sanitation vehicle can perform. This calculation process needs to take into account multiple factors, including remaining load, remaining power, vehicle energy efficiency, cleaning efficiency, etc.

[0076] For the calculation of the maximum additional operating mileage, the system will make an estimate based on the vehicle's energy efficiency and remaining power. For example, if vehicle A can travel 1 kilometer for every 1% of power, the system may reserve 20% of power to ensure safe return to base. Then the maximum additional operating mileage of vehicle A can be calculated as: (50%-20%)*1 kilometer / 1%=30 kilometers.

[0077] The system calculates the maximum additional workload based on the remaining load and the estimated garbage density. For example, if the estimated garbage density is 0.5 tons / cubic meter, the maximum additional workload of vehicle A can be calculated as: 4 cubic meters * 0.5 tons / cubic meter = 2 tons.

[0078] However, the actual maximum additional workload also needs to take into account the maximum additional workload mileage limit. The system needs to estimate whether the amount of garbage that vehicle A can collect within a 30-kilometer driving range exceeds 2 tons. If the estimated result is less than 2 tons, then this estimated result will become the final maximum additional workload.

[0079] S602, determining the additional operation plan of the first sanitation vehicle based on the final position of the first sanitation vehicle after completing the initial operation plan, the maximum additional operation mileage and the maximum additional operation volume that the first sanitation vehicle can perform, the position of the target sub-area with the remaining amount of garbage to be cleaned in the target cleaning area, and the remaining amount of garbage to be cleaned in the target sub-area.

[0080] In one example, the system first needs to integrate various information. This includes the maximum additional operation mileage and the maximum additional operation volume of the first sanitation vehicle obtained in step S601, and the final position of the vehicle after completing the initial operation plan. At the same time, the system also needs to obtain the location information of the target sub-area in the target cleaning area where there is still remaining garbage to be cleaned and the specific amount of remaining garbage to be cleaned.

[0081] For example, suppose the final position of the first sanitation vehicle A after completing the initial operation plan is the coordinate (x, y), its maximum additional operation mileage is 30 kilometers, and the maximum additional operation volume is 2 tons. At the same time, the system detects that there are three target sub-areas (denoted as B, C, and D) in the target cleaning area that still have remaining garbage to be cleaned. Their positions are (x1, y1), (x2, y2), and (x3, y3), and the remaining garbage to be cleaned is 0.8 tons, 1.5 tons, and 0.5 tons, respectively.

[0082] Based on this information, the system performs the following steps to determine the additional work plan for the first sanitation vehicle:

[0083] Calculate distance: The system first calculates the distance from the first sanitation vehicle A to each target sub-area from its final position (x, y). Assume that the calculation result is: 15 kilometers to area B, 25 kilometers to area C, and 10 kilometers to area D.

[0084] Filter accessible areas: The system will filter out the target sub-areas that vehicle A can travel back and forth based on the maximum additional operating mileage (30 kilometers). In this example, areas B and D are both within the accessible range, while area C exceeds half of the maximum operating mileage and is therefore excluded.

[0085] Evaluate cleaning capacity: The system evaluates whether vehicle A has enough remaining loading capacity to handle the garbage in the accessible areas. In this example, the total amount of garbage in areas B and D (0.8+0.5=1.3 tons) is less than the maximum additional workload of vehicle A (2 tons), so vehicle A is capable of cleaning these two areas.

[0086] Route planning: The system will plan the optimal route based on distance, amount of garbage, and possible other factors such as traffic conditions, time windows, etc. In this example, a possible route is to go to the closer area D (10 kilometers) for cleaning, then go to area B (assuming the distance from D to B is 8 kilometers) for cleaning, and finally return to the base or the next designated location.

[0087] Time Estimate: The system estimates the time required to complete this additional work plan, including travel time and cleanup time. This helps ensure that the additional work does not affect the subsequent normal work schedule.

[0088] Determine the final plan: Taking all the above factors into consideration, the system finally determines the additional work plan for vehicle A as follows: starting from (x, y), first go to (x3, y3) to clean up 0.5 tons of garbage in area D, and then go to (x1, y1) to clean up 0.8 tons of garbage in area B. The total driving distance is about 28 kilometers, the total cleaning volume is 1.3 tons, and it is estimated to take 2 hours.

[0089] S603: Use the additional operation plan and the initial operation plan of the first sanitation vehicle as the target operation plan of the first sanitation vehicle.

[0090] S604: Using the initial operation plan of the remaining sanitation vehicles as the target operation plan of the remaining sanitation vehicles.

[0091] After adjusting the initial operation plan of each sanitation vehicle and obtaining the target operation plan of each sanitation vehicle, it also includes:

[0092] Obtain the weather conditions and road traffic conditions in the target area; optimize and adjust the target operation plan of each sanitation vehicle according to the weather conditions and road traffic in the target area to obtain the optimized target operation plan of each sanitation vehicle; send the optimized target operation plan of each sanitation vehicle to the corresponding sanitation vehicle, and control each sanitation vehicle to perform cleaning operations according to the optimized target operation plan.

[0093] In one example, after completing the adjustment of the initial operation plan of each sanitation vehicle and obtaining the target operation plan, the system needs to further consider real-time external factors to ensure the feasibility and efficiency of the operation plan. This additional optimization process mainly includes obtaining the weather conditions and road traffic conditions in the target area, optimizing and adjusting the target operation plan based on these conditions, and finally sending the optimized plan to each sanitation vehicle and controlling its execution. This series of steps is introduced to make the cleaning operation more adaptable to the actual environment and improve the efficiency and safety of the operation.

[0094] First, the system needs to obtain the weather conditions and road traffic conditions in the target area in real time, which can be achieved through data interfaces with meteorological departments and traffic management departments, or by using IoT devices such as sensors installed on the roadside to collect real-time data. For example, the system may obtain a rainfall forecast for the target area in the next 24 hours, with an estimated rainfall of 30 mm, and some roads are partially closed due to construction. This information is crucial for the smooth progress of sanitation operations. Next, the system will optimize and adjust the target operation plan of each sanitation vehicle based on the weather and traffic information obtained. When optimizing, the system will consider a variety of factors and make corresponding adjustments, including weather factors, traffic factors, operation efficiency and safety factors. For example, if rainfall is forecast, the system may adjust the operation sequence and give priority to cleaning low-lying areas that are prone to water accumulation to prevent garbage from flowing with rainwater and causing secondary pollution; for roads that are partially closed due to construction, the system will re-plan the route to avoid congested areas; considering that rainy days may increase the weight and volume of garbage, the system may adjust the expected operation volume of each vehicle; in severe weather conditions, the system may cancel some non-urgent cleaning tasks to ensure the safety of vehicles and operators.

[0095] For a specific sanitation vehicle, for example, sanitation vehicle A, which was originally scheduled to start working at 7 a.m., the system may adjust its working time to 6 a.m. to avoid the predicted rainfall at 8 a.m. At the same time, due to the construction of a main road, the system will plan a new route for vehicle A. Although the distance is slightly longer, it can avoid congested areas and ensure working efficiency. After completing the optimization adjustment, the system will generate optimized target operation plans for each sanitation vehicle. These plans include not only updated routes and schedules, but may also include operating instructions for special weather or traffic conditions. Finally, the system will send these optimized target operation plans to the on-board terminals of each sanitation vehicle through the wireless communication network. After receiving the new operation plan, the on-board terminal will immediately update the display and inform the operator of the change in the plan through voice prompts and other means. At the same time, the system will continue to monitor the execution of each vehicle to ensure that they perform cleaning operations according to the optimized plan.

[0096] After adjusting the initial operation plan of each sanitation vehicle and obtaining the target operation plan of each sanitation vehicle, the method further includes: sending the target operation plan of each sanitation vehicle to the corresponding sanitation vehicle to control each sanitation vehicle to perform the cleaning operation according to its target operation plan; obtaining the cleaning operation execution progress information of each sanitation vehicle, and judging whether there is a second sanitation vehicle with abnormal operation progress according to the cleaning operation execution progress information; if there is a second sanitation vehicle with abnormal operation progress, determining the cause of the abnormal operation of the second sanitation vehicle, and adjusting the target operation plan of the second sanitation vehicle according to the cause of the abnormal operation to obtain an updated target operation plan for the second sanitation vehicle; and sending the updated target operation plan to the second sanitation vehicle so that the second sanitation vehicle performs the cleaning operation according to the updated target operation plan.

[0097] In one example, the target operation plan of each sanitation vehicle is sent to the on-board terminal of the corresponding sanitation vehicle through a wireless communication network. After receiving the operation plan, the on-board terminal will display detailed task information to the operator, including cleaning route, estimated time, operation requirements, etc. At the same time, the system will ensure that each sanitation vehicle starts to perform cleaning operations according to its target operation plan through remote control or instructions. After the operation starts, the system will obtain the cleaning operation execution progress information of each sanitation vehicle in real time. This information may include data such as the real-time location of the vehicle, the area of ​​the completed cleaning area, and the amount of garbage collected. These data are collected through on-board sensors and GPS positioning systems, and transmitted to the central management system in real time through Internet of Things technology. The system will compare the actual progress with the planned progress according to the preset progress standard to determine whether there is a sanitation vehicle with abnormal operation progress (i.e., the second sanitation vehicle).

[0098] For example, if the actual cleaning area of ​​a sanitation vehicle (referred to as vehicle A) is significantly lower than expected, or its position has not changed for a long time, the system will mark it as a second sanitation vehicle that may have abnormal work progress. Once the system identifies the second sanitation vehicle with abnormal work progress, it will immediately start the abnormal analysis process. The system will comprehensively analyze various possible causes of the abnormality, such as vehicle failure, road condition changes, weather impact, operator problems, etc. This analysis process may involve multiple data sources, including fault reports from the on-board diagnostic system, real-time traffic data, weather forecast information, and may even include manual input from operators.

[0099] For example, if vehicle A is identified as having abnormal progress, the system may find that its engine temperature is abnormally high, and combined with the vehicle's location information, it may be due to the vehicle being overloaded due to the steep slope. After determining the cause of the abnormal operation, the system will make corresponding adjustments to the target operation plan of the second sanitation vehicle based on the specific situation. Adjustments may include re-planning the route to avoid problem areas, extending the estimated completion time, reducing the workload, arranging a replacement vehicle, etc.

[0100] In the case of vehicle A, the system might adjust its route to avoid steep slopes and extend the estimated completion time to ensure that the vehicle is not overloaded again. Once the system generates the updated target operation plan, it immediately sends it to the onboard terminal of the second sanitation vehicle. The operator is notified of the plan change and continues the cleaning operation according to the updated plan. At the same time, the system closely monitors the subsequent performance of the second sanitation vehicle to ensure that the problem is effectively resolved.

[0101] Based on the above method, the present application also discloses a sanitation vehicle management device, such as Figure 2 As shown, Figure 2 is a structural diagram of a sanitation vehicle management device provided in an embodiment of the present application, the device comprises: a first acquisition module, a first determination module, a second acquisition module, a second determination module and an output module; wherein,

[0102] The first acquisition module is used to acquire environmental data of multiple areas to be cleaned in the target area, and calculate the cleanliness parameters of the multiple areas to be cleaned based on the environmental data; the first determination module is used to determine the target cleaning areas whose cleanliness parameters among the multiple areas to be cleaned are lower than the preset parameters, and the amount of garbage to be cleaned in the target cleaning areas; the second acquisition module is used to acquire the positions, remaining loads and remaining power of multiple sanitation vehicles in the target area; the second determination module is used to determine the initial operation plan of each sanitation vehicle based on the positions of each sanitation vehicle; the output module is used to adjust the initial operation plan of each sanitation vehicle based on the amount of garbage to be cleaned in the target cleaning area, combined with the remaining load and the remaining power of each sanitation vehicle, to obtain the target operation plan of each sanitation vehicle.

[0103] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0104] See also Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device 1000 may include: at least one processor 1001 , at least one network interface 1004 , a user interface 1003 , a memory 1005 , and at least one communication bus 1002 .

[0105] The communication bus 1002 is used to realize the connection and communication between these components.

[0106] The user interface 1003 may include a display screen (Display) and a camera (Camera), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.

[0107] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0108] Among them, the processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 1001 can integrate one or more combinations of a central processing unit (Central Processing Unit, CPU), a graphics processor (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, and it can be implemented by a single chip.

[0109] Among them, the memory 1005 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 1005 may optionally be at least one storage device located away from the aforementioned processor 1001. As Figure 3 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of a sanitation vehicle management method.

[0110] exist Figure 3 In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1001 can be used to call an application program storing a sanitation vehicle management method in the memory 1005. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0111] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more of the methods described in the above embodiments.

[0112] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0113] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0114] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0115] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0116] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0117] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0118] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A sanitation vehicle management method, characterized in that: The method comprises: Obtain environmental data of multiple areas to be cleaned in the target area, and calculate the clean parameters of the multiple areas to be cleaned according to the environmental data; the environmental data includes garbage types and garbage coverage areas, and the clean parameters of the multiple areas to be cleaned are calculated, including: substituting the garbage types and garbage coverage areas into a preset formula to calculate the clean parameters of the multiple areas to be cleaned; wherein, Wherein, P is the cleanliness parameter of each area to be cleaned, K is the preset parameter, C i is the cleaning difficulty coefficient of the i-th type of garbage, A i is the garbage coverage area of ​​the i-th type of garbage, S i is the garbage impact parameter corresponding to the i-th type of garbage; Determine a target cleaning area among the multiple areas to be cleaned, wherein the cleaning parameter is lower than a preset parameter, and the amount of garbage to be cleaned in the target cleaning area; Obtaining the positions, remaining loads, and remaining power of multiple sanitation vehicles in the target area; Determining an initial operation plan for each of the sanitation vehicles according to the position of each of the sanitation vehicles; Based on the amount of garbage to be cleaned in the target cleaning area, combined with the remaining load capacity and the remaining power of each sanitation vehicle, the initial operation plan of each sanitation vehicle is adjusted to obtain a target operation plan for each sanitation vehicle.

2. The sanitation vehicle management method according to claim 1, characterized in that: Determining the initial operation plan of each sanitation vehicle according to the position of each sanitation vehicle includes: Acquire the road network information in the target area, and calculate the distance from each sanitation vehicle to the target cleaning area according to the position of each sanitation vehicle and the road network information; According to the distance that each sanitation vehicle reaches the target cleaning area, a route for each sanitation vehicle to travel to the target cleaning area is determined, and the route for each sanitation vehicle to travel to the target cleaning area is used as an initial operation plan for each sanitation vehicle.

3. The sanitation vehicle management method according to claim 1, characterized in that: Based on the amount of garbage to be cleaned in the target cleaning area, combined with the remaining load and the remaining power of each sanitation vehicle, the initial operation plan of each sanitation vehicle is adjusted to obtain a target operation plan of each sanitation vehicle, including: Calculating the final remaining load and final remaining power of each of the sanitation vehicles after completing the initial operation plan, as well as the remaining amount of garbage to be cleaned in the target cleaning area; In combination with the final remaining load capacity, the final remaining power and the remaining amount of garbage to be cleaned in the target cleaning area of ​​each sanitation vehicle, the initial operation plan of each sanitation vehicle is adjusted to obtain a target operation plan of each sanitation vehicle.

4. The sanitation vehicle management method according to claim 3, characterized in that: The initial operation plan of each sanitation vehicle is adjusted based on the final remaining load, the final remaining power and the remaining amount of garbage to be cleaned in the target cleaning area of ​​each sanitation vehicle to obtain a target operation plan of each sanitation vehicle, including: Determine a first sanitation vehicle with additional operating capacity according to the final remaining load and the final remaining power of each sanitation vehicle, and calculate the maximum additional operating mileage and maximum additional operating volume that can be performed by the first sanitation vehicle; Determine an additional operation plan for the first sanitation vehicle based on the final position of the first sanitation vehicle after completing the initial operation plan, the maximum additional operation mileage and the maximum additional operation volume that the first sanitation vehicle can perform, the position of the target sub-area in the target cleaning area where the remaining amount of garbage to be cleaned exists, and the remaining amount of garbage to be cleaned in the target sub-area; using the additional operation plan of the first sanitation vehicle and the initial operation plan as the target operation plan of the first sanitation vehicle; The initial operation plan of the remaining sanitation vehicles is used as the target operation plan of the remaining sanitation vehicles.

5. The sanitation vehicle management method according to claim 1, characterized in that: After the initial operation plan of each sanitation vehicle is adjusted to obtain the target operation plan of each sanitation vehicle, the method further includes: Obtaining weather conditions and road traffic conditions in the target area; According to the weather conditions and road traffic in the target area, the target operation plan of each sanitation vehicle is optimized and adjusted to obtain an optimized target operation plan of each sanitation vehicle; The optimized target operation plan of each sanitation vehicle is sent to the corresponding sanitation vehicle, and each sanitation vehicle is controlled to perform the cleaning operation according to the optimized target operation plan.

6. The sanitation vehicle management method according to claim 1, characterized in that: After the initial operation plan of each sanitation vehicle is adjusted to obtain the target operation plan of each sanitation vehicle, the method further includes: sending the target operation plan of each sanitation vehicle to the corresponding sanitation vehicle, and controlling each sanitation vehicle to perform cleaning operations according to its target operation plan; Acquire the cleaning operation execution progress information of each of the sanitation vehicles, and determine whether there is a second sanitation vehicle with abnormal operation progress according to the cleaning operation execution progress information; If there is a second sanitation vehicle with abnormal operation progress, determine the cause of the abnormal operation of the second sanitation vehicle, and adjust the target operation plan of the second sanitation vehicle according to the cause of the abnormal operation to obtain an updated target operation plan of the second sanitation vehicle; The updated target operation plan is sent to the second sanitation vehicle so that the second sanitation vehicle performs the cleaning operation according to the updated target operation plan.

7. A sanitation vehicle management device, characterized in that: The device comprises: a first acquisition module, a first determination module, a second acquisition module, a second determination module and an output module; wherein, The first acquisition module is used to acquire environmental data of multiple areas to be cleaned in the target area, and calculate the clean parameters of the multiple areas to be cleaned according to the environmental data; the calculation of the clean parameters of the multiple areas to be cleaned according to the environmental data, wherein the environmental data includes garbage types and garbage coverage areas, comprises: substituting the garbage types and garbage coverage areas into a preset formula to calculate the clean parameters of the multiple areas to be cleaned; wherein, Wherein, P is the cleanliness parameter of each area to be cleaned, K is the preset parameter, C i is the cleaning difficulty coefficient of the i-th type of garbage, A i is the garbage coverage area of ​​the i-th type of garbage, S i is the garbage impact parameter corresponding to the i-th type of garbage; The first determination module is used to determine a target cleaning area among the multiple areas to be cleaned, wherein the cleaning parameter is lower than a preset parameter, and the amount of garbage to be cleaned in the target cleaning area; The second acquisition module is used to obtain the positions, remaining loads and remaining power of multiple sanitation vehicles in the target area; the second determination module is used to determine the initial operation plan of each sanitation vehicle according to the position of each sanitation vehicle; The output module is used to adjust the initial operation plan of each sanitation vehicle based on the amount of garbage to be cleaned in the target cleaning area and in combination with the remaining load capacity and the remaining power of each sanitation vehicle to obtain a target operation plan for each sanitation vehicle.

8. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 6.

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