A material distribution service scheduling and management system based on the collaboration of drones and vehicles

Abstract

The present invention claims protection for a scheduling and management system for material distribution services based on the collaboration of unmanned aerial vehicles and vehicles, which relates to the technical field of material distribution. It includes: a material management module, an algorithm operation module, an algorithm performance comparison module, an algorithm comparison visualization module, and a distribution management module. The material management module is used to manage materials; the algorithm operation module is used to process and analyze the selected logistics data and obtain the transportation route information of the collaboration between unmanned aerial vehicles and vehicles in combination with the actual traffic topology, and display the route map under different numbers of users; the algorithm performance comparison module is used to compare the performance of other algorithms; the algorithm comparison visualization module is used to display and draw a visual comparison map of the routes for comparison in different traffic environments and at different collection points; the distribution management module is used to select the distribution materials, and obtain the distribution site and distribution logistics information in real time, and visually display them in the form of charts.

Description

Technical Field

[0001] The present invention relates to the technical field of material distribution service scheduling management systems, and particularly to a material distribution service scheduling management system that coordinates drones and vehicles. Background Art

[0002] The continuous intensification of the modern unmanned trend has made the application of drones in the military field become increasingly important, and they can undertake various types of tasks such as reconnaissance and detection, tracking and positioning, precise guidance, electromagnetic interference, and material delivery. The accurate and reliable execution of drone tasks depends on a reasonable and efficient management and control mechanism, that is, according to various constraint conditions such as the environmental information perceived by the drone, task requirements, and on-board task loads, through comprehensive analysis of task elements, optimizing the scheduling and coordination of various resources, determining the strategies for drone task perception, network communication, routing transmission, and trajectory planning, to ensure that the drone efficiently completes tasks in the best way.

[0003] With the development of electronic information technology and the improvement of the informatization and intelligence level of drones, the task perception execution environment and mode of drones have undergone profound changes, especially the wide-area high-dynamics of the task execution environment and the complex diversification of task requirements. Driven by the goals of "carbon peak and carbon neutrality" and "contactless distribution", drone and vehicle distribution, as a new type of material distribution method, has entered the military field following the trend of the unmanned era and has received high attention from the country. This system can support both military integrated communication, sensing, and computing collaborative intelligent combat platforms and civilian logistics distribution that coordinates drones and vehicles and air-land resource coordination.

[0004] CN114677087A, a method for collaborative distribution of vehicle combination drones, predicts the logistics order prediction information within a future period through a sales prediction method based on a meta-learning framework, which is used to plan the logistics scheduling plan and logistics distribution plan. For the logistics scheduling plan, the present invention determines the distribution plan according to the height difference between different path nodes and uses a delay time penalty function to optimize the logistics scheduling plan. At the same time, the present invention also uses a drone vehicle path optimization model to optimize the logistics distribution path and optimizes the drone vehicle path optimization model through a linear relaxation optimization algorithm. The scheme is as follows: obtaining the logistics order prediction information; planning the logistics scheduling plan and logistics distribution path based on the logistics order prediction information; optimizing the logistics scheduling plan and logistics distribution path; and performing logistics distribution according to the optimized logistics scheduling plan and logistics distribution path.

[0005] The CN114677087A patent focuses on proposing a formulaic solution for logistics distribution, staying only at the theoretical formula derivation and not considering the practical value and effectiveness of its solution. In contrast, this patent focuses on proposing a logistics distribution management system that applies the proposed algorithm, combined with real traffic topology using front-end and back-end technologies, to actual logistics, and compares the practical value obtained from the operation results of the CMDSS algorithm proposed in this patent with those of other related algorithms to demonstrate the effectiveness of the algorithm. Summary of the Invention

[0006] The present invention aims to solve the problems of the above prior art. A material distribution service scheduling management system based on the cooperation of unmanned aerial vehicles (UAVs) and vehicles is proposed. The technical solution of the present invention is as follows:

[0007] A material distribution service scheduling management system based on the cooperation of UAVs and vehicles, which includes: a material management module, an algorithm operation module, an algorithm performance comparison module, an algorithm comparison visualization module, and a distribution management module. The material management module is used to manage materials, including performing real-time operations of adding, deleting, modifying, and querying material information, and visually displaying the inventory materials and historical material data in the form of charts; the algorithm operation module is used to process and analyze the selected logistics data and combine the actual traffic topology to obtain the transportation route information of the cooperation between UAVs and vehicles, and display the route map under different numbers of users; the algorithm performance comparison module is used to compare the performance of other algorithms, compare the performance of other two algorithms based on different numbers of users, different payloads of UAVs, and different user requirements, and consider the algorithm for the coordination of UAV and vehicle material distribution services scheduling (CMDSS) designed in the present invention. From the perspective of cost, under the condition of minimizing the vehicle driving distance, maximize the ratio of the UAV flight distance to the vehicle driving distance, and draw a comparison graph; the algorithm comparison visualization module is used to display the quantitative index graph obtained by comparing this algorithm with other algorithms, compare and draw a line visualization comparison graph under different traffic environments and different collection points, and compare with the UAV and vehicle coordinated transportation routes obtained by other related algorithms to ensure the minimum number of UAVs and vehicles are dispatched and the running time and distance are the shortest; the distribution management module is used to select the distribution materials, and obtain the distribution site and distribution logistics information in real time, and visually display them in the form of charts.

[0008] Furthermore, the material management module includes a real-time material inventory display module, a historical material data module, a material information addition module, a material information deletion module, a material information modification module, and a material information viewing module; among them,

[0009] The real-time display of material inventory module is used to visually display the existing material inventory in the form of a pie chart;

[0010] The historical material data module is used to dynamically display the daily historical data, including the data of the distributed materials and the total quantity of materials, in the form of a drag-and-drop line chart.

[0011] The add material information module, delete material information module, modify material information module and view material information module are respectively used to add, delete, modify and view the material information in real time.

[0012] Furthermore, the algorithm operation module includes an algorithm theory module, a real-time algorithm module, and a historical data algorithm module;

[0013] The algorithm theory module is used to visually display the theoretical path diagrams of the deep reinforcement learning algorithm in 20, 30, and 50 candidate route data sets;

[0014] The real-time algorithm module is used to run the algorithm in real time after selecting the material data set, and combine with the traffic topology to generate the route results in real time;

[0015] The historical data algorithm module is used to generate the corresponding logistics data set after selecting the corresponding date and its time period, and then call the implementation algorithm to obtain the route plan;

[0016] Furthermore, the algorithm performance comparison module includes a performance comparison module based on different numbers of users, a performance comparison module based on different payloads of drones, and a performance comparison module based on different user requirements; among them,

[0017] The performance comparison module based on different numbers of users is used to draw a comparison bar chart of the total flight distance of drones and the total driving distance of vehicles when the number of customers is 20, 30, and 50 for the algorithm used in this system and two other comparison algorithms, and draw a comparison chart of the ratio of the total flight distance of drones to the total driving distance of vehicles when the number of customers is different;

[0018] The performance comparison module based on different payloads of drones is used to draw a comparison line chart of the total flight distance of drones and the total driving distance of vehicles when the maximum payloads of drones are 8kg, 9kg, 10kg, 11kg, and 12kg for the algorithm used in this system and two other comparison algorithms, and draw a comparison chart of the ratio of the total flight distance of drones to the total driving distance of vehicles when the maximum payloads of drones are different;

[0019] The performance comparison module based on different user requirements is used to draw a comparison line chart of the total flight distance of the drone and the total driving distance of the vehicle when the algorithms used in this system and two other comparison algorithms are applied under the customer requirements of 1 kg, 2 kg, 3 kg, 4 kg, and 5 kg respectively, and also draw a comparison chart of the ratio of the total flight distance of the drone to the total driving distance of the vehicle under different customer requirements.

[0020] Furthermore, the algorithm comparison visualization module includes a comparison visualization module under different traffic environments, a comparison visualization module under different numbers of customers, a comparison module for the number of operating devices, a comparison module for operating costs, a comparison module for the ratio of operating distances, and a comparison module for operating times;

[0021] The comparison visualization module under different traffic environments refers to applying the algorithms used in this system and a comparison algorithm to the real maps of Hangzhou and Chengdu respectively, and combining the traffic topology map to compare the collaborative transportation routes of the drones and vehicles obtained, and drawing a visual comparison chart;

[0022] The comparison visualization module under different numbers of customers refers to applying the algorithms used in this system and a comparison algorithm to the real maps with different numbers of collection points, and combining the traffic topology map to compare the collaborative transportation routes of the drones and vehicles obtained, and drawing a visual comparison chart;

[0023] The comparison chart module for the number of operating devices refers to the comparison of the number of drones and vehicles required for the operating routes obtained by different algorithms in the comparison charts based on different traffic environments and different numbers of customers;

[0024] The comparison module for operating costs refers to the comparison of the operating costs required in the comparison charts based on different traffic environments and different numbers of customers. The calculation of the operating cost is specifically 1 yuan per kilometer for vehicle driving and 0.5 yuan per kilometer for drone driving;

[0025] The comparison module for operating times refers to the comparison of the operating times required for the transportation routes obtained by different algorithms in the comparison charts based on different traffic environments and different numbers of customers.

[0026] Furthermore, the distribution management module includes a historical material selection module, a real-time updated delivery site module, a real-time obtained distribution material information module, a distribution site statistics module, and a material route visualization module; among them,

[0027] The material dataset selection module is used to select the daily dataset and then run the CMDSS algorithm to obtain the real-time route result;

[0028] The real-time updated delivery site module is used to update the information of the delivered sites in real time;

[0029] The module for real-time obtaining of distribution material information is used to update the information of the materials being delivered in real time;

[0030] The module for statistics of material distribution sites is used to count the historical material distribution sites and visually display them using a frequency scatter plot; the module for visualization of material routes is used to dynamically and visually display the route results run by the algorithm.

[0031] The advantages and beneficial effects of the present invention are as follows:

[0032] 1. The functions of the present invention are novel: The scheduling management system proposed by the present invention not only realizes material management, but also realizes the scheduling and path planning management of drones and vehicle materials. This management system can support both military integrated communication, sensing and computing collaborative intelligent combat platforms and civilian logistics distribution with collaborative drones and vehicles and air-land resource collaboration.

[0033] 2. Adapt to scenarios with a large number of customers: Figure 7 From left to right are the relationships between the ratio of the total flight distance of drones to the total driving distance of vehicles, the total driving distance of vehicles, and the total flight distance of drones under the conditions of different numbers of users. It can be seen from these three comparison pictures that when the number of users is 20, 30, and 50 respectively, the ratio of the driving distance of drones and vehicles of the CMDSS algorithm is higher than that of the reinforcement learning algorithm, and the driving distance of vehicles of the CMDSS algorithm is less than that of the deep reinforcement learning algorithm and the greedy algorithm. And as the number of customers continues to increase, these two gaps become more obvious. Therefore, considering factors such as cost, when the number of customers is large, the number of vehicles used is small, and the flight routes of drones are reasonable, the CMDSS algorithm shows the best performance, indicating that our algorithm is more adaptable to scenarios with a large number of customers.

[0034] 3. Applicable to the maximum payloads of different drones: Figure 8 From left to right are the relationships between the ratio of the total flight distance of drones to the total driving distance of vehicles, the total driving distance of vehicles, and the total flight distance of drones under the conditions of different maximum payloads of drones. It can be seen from these three line graph comparison pictures that the ratio of the flight distance of drones to the driving distance of vehicles of the CMDSS algorithm and the greedy algorithm is close under the conditions of different maximum payloads of drones, and both are greater than the ratio of the flight distance of drones to the driving distance of vehicles of the deep reinforcement learning algorithm, while the driving distance of vehicles is slightly lower than that of the greedy algorithm. Therefore, the CMDSS algorithm is applicable to the maximum payloads of various drones.

[0035] 4. The effectiveness of the CMDSS algorithm: Figure 9From left to right are the relationships among the ratio of the total flight distance of the drone to the total driving distance of the vehicle, the total driving distance of the vehicle, and the total flight distance of the drone under the customer's requirements. Since the light-demand packages of the transported materials account for a relatively large proportion in the total amount, when the customer's demand is between 1.0 kg and 3.0 kg, the total flight distance of the drone and the total driving distance of the vehicle show a faster downward trend; the driving distance of the vehicle is also significantly lower than that of the other two algorithms. This proves the effectiveness of the CMDSS algorithm under small payload conditions.

[0036] 5. Advantages of the system in actual traffic: Figure 13 In a, b, and c, they represent the comparison diagrams of two algorithms with different quantities in different regions, which are the comparison diagrams of the actual traffic topologies of 13 data nodes in Hangzhou, 17 data nodes in Chengdu, and 25 data nodes in Hangzhou, respectively. Taking Figure a as an example, from left to right are the number of vehicles, the number of drones, the total driving distance of the vehicle and the drone, the sum of the driving vehicles, and the comparison of the driving costs using the CMDSS and DRL algorithms. It can be seen from the figure that under the same nodes, the CMDSS algorithm has more advantages than DRL in terms of the number of input devices, driving distance, driving time, and driving cost, and the CMDSS algorithm is more advantageous.

[0037] The innovation points of the present invention are mainly in the algorithm operation module, the algorithm performance comparison module, and the algorithm comparison visualization module. Among them, the CMDSS algorithm used in the algorithm operation module is obtained by improving the greedy algorithm; through the algorithm performance comparison module, the performance of the CMDSS algorithm is compared with that of the DRL algorithm and the greedy algorithm to demonstrate the superiority of the CMDSS algorithm; and through the front-end and back-end technologies, the CMDSS algorithm is applied to the material distribution service scheduling system of the cooperation between the drone and the vehicle, and combined with the real traffic topology for simulation and quantitative comparison to demonstrate the practical value of the system in actual traffic. Description of the Drawings

[0038] Figure 1 It is a schematic diagram of the system function module framework of the preferred embodiment provided by the present invention

[0039] Figure 2 It is a schematic diagram of the material management module of the present invention

[0040] Figure 3 It is a schematic diagram of the process of the material management module of the present invention

[0041] Figure 4 It is a theoretical operation diagram of 20 data nodes of the present invention

[0042] Figure 5 It is a theoretical operation diagram of 30 data nodes of the present invention

[0043] Figure 6 Calculate the theoretical operation diagram for the 50 data nodes of the present invention

[0044] Figure 7 This is a bar chart comparing the performance of different numbers of users of the present invention.

[0045] Figure 8 This is a performance comparison chart based on different maximum loads of drones in the present invention.

[0046] Figure 9 This is a performance comparison chart based on different user requirements of the present invention

[0047] Figure 10 Comparison of the actual traffic topology of 13 data nodes in Hangzhou using the two algorithms in this invention

[0048] Figure 11 Comparison of the actual traffic topology of 17 data nodes in Chengdu using the two algorithms in this invention

[0049] Figure 12 Comparison of the actual traffic topology of 25 data nodes in Hangzhou using the two algorithms in this invention

[0050] Figure 13 For the present invention Figure 10 , Figure 11 and Figure 12 Quantitative histogram for comparison

[0051] Figure 14 Schematic diagram of the distribution management module

[0052] Figure 15 Flow chart of the distribution management module DETAILED DESCRIPTION

[0053] The following will describe the technical solutions in the embodiments of the present invention in detail with reference to the accompanying drawings. The described embodiments are only a part of the embodiments of the present invention.

[0054] The technical solution of the present invention to solve the above technical problems is:

[0055] The following is a summary of the functions of the material distribution service scheduling and management system based on the collaboration of drones and vehicles:

[0056] like Figure 1As shown in the figure, the material distribution service scheduling and management system based on the cooperation of drones and vehicles includes a material management module, an algorithm operation module, an algorithm performance comparison module, an algorithm comparison visualization module, and a distribution management module. Among them, the material management module is used to manage military materials, including real-time operations of adding, deleting, modifying, and querying material information, and visually displaying the stored materials and historical material data in the form of charts; the algorithm operation module uses algorithms to process and analyze the selected logistics data and combines the actual traffic topology to obtain the transportation route information of the cooperation between drones and vehicles, and displays the route map under different numbers of users; the algorithm performance comparison module is used to compare the performance of other algorithms, and compare the performance of the other two algorithms based on different numbers of users, different payloads of drones, and different user requirements. Considering from the perspective of cost, specifically, it is to maximize the ratio of the flight distance of the drone to the driving distance of the vehicle under the condition of the minimum driving distance of the vehicle, and draw its comparison chart; the algorithm comparison visualization module is used to display the quantitative index chart obtained by comparing this algorithm with other algorithms, compare and draw the route visualization comparison chart in different traffic environments and different collection points, and compare with the collaborative transportation routes of drones and vehicles obtained by other relevant algorithms to ensure the least number of drones and vehicles for scheduling and the shortest running time and distance; the distribution management module is used to select the distribution materials, and real-time obtain the distribution site and distribution logistics information, and visually display it in the form of charts.

[0057] 1. Material Management Module

[0058] 1) Real-time Display of Material Inventory Module: Visually display the existing material inventory in the form of a pie chart.

[0059] 2) Historical Material Data Module: Used to dynamically display the daily historical data, including the distributed material data and the total quantity of materials, in the form of a drag-and-drop line chart.

[0060] 2. Algorithm Operation Module

[0061] 1) Algorithm Theory Module: Used to visually display the theoretical path diagrams of this deep reinforcement learning algorithm for 20, 30, and 50 candidate route data sets;

[0062] 2) Real-time Algorithm Module: Used to run the algorithm in real time after selecting the material data set, and combine the traffic topology to generate the route results in real time;

[0063] 3) Historical Data Algorithm Module: Used to generate the corresponding logistics data set after selecting the corresponding date and its time period, and then call the implementation algorithm to obtain the route plan;

[0064] 3. The Algorithm Performance Comparison Module

[0065] 1) Performance comparison module based on different numbers of users: It is used to draw a comparison bar chart of the total flight distance of drones and the total driving distance of vehicles for the algorithm used in this system and two other comparison algorithms when the number of customers is 20, 30, and 50, and also draw a comparison chart of the ratio of the total flight distance of drones to the total driving distance of vehicles under different numbers of customers;

[0066] 2) Performance comparison module based on different payloads of drones: It is used to draw a comparison line chart of the total flight distance of drones and the total driving distance of vehicles for the algorithm used in this system and two other comparison algorithms when the maximum payloads of drones are 8 kg, 9 kg, 10 kg, 11 kg, and 12 kg respectively, and also draw a comparison chart of the ratio of the total flight distance of drones to the total driving distance of vehicles under different maximum payloads of drones;

[0067] 3) The performance comparison based on different numbers of users: It is used to draw a comparison line chart of the total flight distance of drones and the total driving distance of vehicles for the algorithm used in this system and two other comparison algorithms when the customer demands are 1 kg, 2 kg, 3 kg, 4 kg, and 5 kg respectively, and also draw a comparison chart of the ratio of the total flight distance of drones to the total driving distance of vehicles under different customer demands;

[0068] 4. The algorithm comparison visualization module

[0069] 1) Comparison visualization module under different traffic environments: It means applying the algorithm used in this system and a comparison algorithm to the real maps of Chengdu and Hangzhou respectively, and comparing the collaborative transportation routes of drones and vehicles obtained in combination with the traffic topology map, and drawing a visualization comparison chart;

[0070] 2) Comparison visualization module for different numbers of customers: It means applying the algorithm used in this system and a comparison algorithm to the real maps of different collection points in Hangzhou respectively, and comparing the collaborative transportation routes of drones and vehicles obtained in combination with the traffic topology map, and drawing a visualization comparison chart;

[0071] 3) Operation equipment quantity comparison chart module: It means the comparison of the quantities of drones and vehicles required for the operation routes obtained by different algorithms in the comparison charts based on different traffic environments and different numbers of customers;

[0072] 4) Operation cost comparison module: It means the comparison of the operation costs required in the comparison charts based on different traffic environments and different numbers of customers. Since the operation cost of drones is relatively low, the specific calculation of the operation cost is 1 yuan per kilometer for vehicle driving and 0.5 yuan per kilometer for drone driving;

[0073] 5) Running time comparison module: It refers to the comparison of the running times required for the transportation routes obtained by different algorithms in the comparison charts based on different traffic environments and different numbers of customers.

[0074] 6. Distribution management module

[0075] 1) The historical material selection module is used to select the daily data set to run the algorithm and obtain the real-time route result.

[0076] 2) Real-time update delivery site module: It is used to update the information of the delivered sites in real time.

[0077] 3) Real-time acquisition of distribution material information module: It will be used to update the information of the materials being delivered in real time.

[0078] 4) Material distribution site statistics module: It is used to count the historical material distribution sites of the current month and visually display them using a frequency scatter plot.

[0079] 5) Material route visualization module: It is used to dynamically visualize the route results obtained by the algorithm.

[0080] The systems, devices, modules or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0081] It should also be noted that the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. Without further limitations, the element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, commodity or device including the said element.

[0082] The above embodiments should be understood as being only used to illustrate the present invention and not to limit the protection scope of the present invention. After reading the content recorded in the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. A material distribution service scheduling and management system based on the collaboration of drones and vehicles, characterized in that, Including: A material management module, an algorithm operation module, an algorithm performance comparison module, an algorithm comparison visualization module, and a distribution management module. The material management module is used to manage materials, including performing real-time operations of adding, deleting, modifying, and querying material information, and visually displaying the stored materials and historical material data in the form of charts; The algorithm operation module is used to process and analyze the selected logistics data, and combine the actual traffic topology to obtain the transportation route information of the cooperation between drones and vehicles, and display the route map under different numbers of users; The algorithm performance comparison module is used to compare the performance of other algorithms. The designed CMDSS algorithm for the scheduling of the material distribution service based on the cooperation between drones and vehicles is used to compare the performance of the deep reinforcement learning algorithm and the greedy algorithm based on different numbers of users, different payloads of drones, and different demands of users. Considering from the perspective of cost, under the condition of the minimum driving distance of the vehicle, the ratio of the flight distance of the drone to the driving distance of the vehicle is maximized, and its comparison chart is drawn. The algorithm comparison visualization module is used to display the quantitative index chart obtained by comparing this algorithm with other algorithms, make comparisons under different traffic environments and different collection points and draw the route visualization comparison chart, and compare it with the transportation routes of the cooperation between drones and vehicles obtained by other related algorithms to ensure that the minimum number of drones and vehicles is scheduled and the running time and distance are the shortest. The distribution management module is used to select the distribution materials, and obtain the distribution site and distribution logistics information in real time, and visually display them in the form of charts; The algorithm operation module includes an algorithm theory module, a real-time algorithm module, and a historical data algorithm module; among them, The algorithm theory module is used to visually display the theoretical path charts of the deep reinforcement learning algorithm in 20, 30, and 50 candidate route data sets; The real-time algorithm module is used to run the algorithm in real time after selecting the material data set, and combine the traffic topology to generate the route result in real time; The historical data algorithm module is used to generate the corresponding logistics data set after selecting the corresponding date and its time period, and then call the implementation algorithm to obtain the route plan.

2. The material distribution service scheduling and management system based on the cooperation of drones and vehicles according to claim 1, characterized in that The material management module includes a real-time display of material inventory module, a historical material data module, an add material information module, a delete material information module, a modify material information module, and a view material information module; among them, The real-time display of material inventory module is used to visually display the existing material inventory in the form of a pie chart; The historical material data module is used to dynamically display the daily historical data, including the distributed material data and the total quantity of materials, in the form of a drag line chart; The add material information module, the delete material information module, the modify material information module, and the view material information module are respectively used to perform the operations of adding, deleting, modifying, and viewing material information in real time.

3. The material distribution service scheduling and management system based on the collaboration of drones and vehicles according to claim 1, wherein, The algorithm performance comparison module includes a performance comparison module based on different numbers of users, a performance comparison module based on different payloads of drones, and a performance comparison module based on different demands of users; among them, The performance comparison module based on different numbers of users is used to draw a comparison bar chart of the total flight distance of drones and the total driving distance of vehicles for the algorithm used in this system and two other comparison algorithms when the number of customers is 20, 30, and 50, and also draw a comparison chart of the ratio of the total flight distance of drones to the total driving distance of vehicles under different numbers of customers; The performance comparison module based on different payloads of drones is used to draw a comparison line chart of the total flight distance of drones and the total driving distance of vehicles for the algorithm used in this system and two other comparison algorithms when the maximum payloads of drones are 8 kg, 9 kg, 10 kg, 11 kg, and 12 kg respectively, and also draw a comparison chart of the ratio of the total flight distance of drones to the total driving distance of vehicles under different maximum payloads of drones; The performance comparison module based on different customer requirements is used to draw a comparison line chart of the total flight distance of drones and the total driving distance of vehicles for the algorithm used in this system and two other comparison algorithms when the customer requirements are 1 kg, 2 kg, 3 kg, 4 kg, and 5 kg respectively, and also draw a comparison chart of the ratio of the total flight distance of drones to the total driving distance of vehicles under different customer requirements; 4. A material distribution service scheduling and management system based on the collaboration of drones and vehicles according to claim 1, characterized in that, The algorithm comparison visualization module includes a comparison visualization module under different traffic environments, a comparison visualization module under different numbers of customers, a comparison module for the number of operating devices, a comparison module for operating costs, a comparison module for the ratio of operating distances, and a comparison module for operating times; The comparison visualization module under different traffic environments refers to applying the algorithm used in this system and a comparison algorithm to the real maps of Hangzhou and Chengdu respectively, and comparing the collaborative transportation routes of drones and vehicles obtained in combination with the traffic topology map, and drawing a visualization comparison chart; The comparison visualization module under different numbers of customers refers to applying the algorithm used in this system and a comparison algorithm to the real maps with different numbers of collection points, and comparing the collaborative transportation routes of drones and vehicles obtained in combination with the traffic topology map, and drawing a visualization comparison chart; The comparison chart module for the number of operating devices refers to the comparison of the number of drones and vehicles required for the operating routes obtained by different algorithms in the comparison charts based on different traffic environments and different numbers of customers; The operating cost comparison module refers to the comparison of the operating costs required in the comparison charts based on different traffic environments and different numbers of customers. The calculation of the operating cost is specifically 1 yuan per kilometer for vehicle driving and 0.5 yuan per kilometer for drone driving; The operating time comparison module refers to the comparison of the operating times required for the transportation routes obtained by different algorithms in the comparison charts based on different traffic environments and different numbers of customers; 5. The material distribution service scheduling and management system based on the cooperation of drones and vehicles according to claim 1, characterized in that, The distribution management module includes a historical material selection module, a real-time updated delivery site module, a real-time obtained distribution material information module, a material distribution site statistics module, and a material route visualization module; among them, The material dataset selection module is used to select the daily dataset and then run the CMDSS algorithm to obtain the real-time route result; The real-time updated delivery site module is used to update the information of the delivered sites in real time; The real-time acquisition of distribution material information module is used to update the information of the materials being delivered in real time; The material distribution site statistics module is used to count the historical material distribution sites and visually display them using a frequency scatter plot; the material route visualization module is used to dynamically and visually display the route results obtained by the algorithm.

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