Canal channel construction earthwork stone intelligent scheduling and transporting method and system

Abstract

The invention discloses a canal channel construction earthwork stone intelligent scheduling transportation method and system, and particularly relates to the technical field of channel construction, and the system comprises a resource pool construction module, a transportation equipment bidding generation module, a transportation task intelligent matching module, and a transportation task execution and optimization module. According to the method, the transport capacity resource pool and the task order pool based on the block chain are constructed, the equipment intelligent agent generates differentiated quotation based on a built-in cost model, the predefined algorithm is executed by running at the edge computing node, the equipment is subjected to order global matching, then the optimal transport equipment is matched, and in the task process of the transport equipment, the task efficiency of the transport equipment is improved. Based on releasing and sensing virtual pheromones to the virtual pheromone map where the intelligent agent is located, self-organized path optimization and dynamic updating of the pheromone map are carried out, resources can flow to reasonable and efficient task points, the scheduling efficiency is improved, and the method is suitable for linear engineering scenes such as canal channel construction which is large in range, large in environment variable number and poor in network condition.

Description

Technical Field

[0001] This invention relates to the field of waterway construction technology, and more specifically, to an intelligent scheduling and transportation method and system for earthwork and stone in canal waterway construction. Background Technology

[0002] Leveraging cutting-edge information technologies such as the Internet of Things, big data, artificial intelligence, cloud computing, and GPS, an intelligent material transportation management system covering the entire process of canal and waterway construction is constructed. By collecting and analyzing core data such as vehicle trajectories, ship navigation status, and dynamic changes in loading volume in key material transportation links such as earthwork and stone, and combining intelligent algorithm models, the system achieves precise scheduling and route optimization management of transportation resources. Ultimately, it achieves the goal of maximizing transportation efficiency, minimizing cost input, minimizing energy consumption, and optimizing the safety factor for intelligent scheduling and transportation of earthwork and stone in canal and waterway construction, providing efficient, green, and safe technical support for modern waterway engineering construction.

[0003] However, in practical use, it still has some shortcomings. For example, the existing canal and waterway construction operation scheduling technology mostly adopts a centralized control mode, in which dispatchers or central algorithms assign tasks according to fixed rules. This mode is rigid and lacks autonomous optimization capabilities: it cannot efficiently cope with sudden interference such as vehicle failures, road congestion, and weather changes; it has poor coordination: it is difficult for transportation units to share and allocate transportation capacity efficiently, which easily leads to "information silos" and waste of transportation capacity; and it lacks incentive mechanisms: it cannot effectively motivate drivers to choose the optimal route and complete emergency tasks. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an intelligent scheduling and transportation method and system for earthwork and stone in canal construction, which addresses the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent scheduling and transportation system for earthwork and stone in canal construction, comprising: Resource pool construction module: The transportation equipment uploads its capacity information to a shared capacity resource pool through the vehicle terminal after encryption. The construction party publishes the transportation task to the task order pool in the form of a blockchain smart contract.

[0006] Transportation Equipment Bidding Generation Module: The intelligent agent for idle transportation equipment continuously scans the task order pool, conducts demand bidding for tasks based on the built-in cost model of the intelligent agent, and generates differentiated quotations for different transportation equipment for tasks in the task order pool.

[0007] Intelligent matching module for transportation tasks: The market clearing and settlement algorithm running on edge computing nodes matches tasks according to predefined rules of blockchain smart contracts, matches the optimal transportation equipment, and generates a blockchain record.

[0008] Transportation task execution and optimization module: During the task execution process, the transportation equipment releases and senses virtual pheromones to the virtual pheromone map where it is located based on the intelligent agent, and performs self-organized path optimization and dynamic updates of the pheromone map.

[0009] Preferably, the resource pool construction module specifically comprises: The transportation capacity resource pool stores transportation capacity information including the real-time location, load status, load capacity, equipment type, affiliated unit, and reputation value of transportation equipment. All information is encrypted and uploaded to the blockchain network to ensure that the data is tamper-proof and traceable. The blockchain smart contract defines the origin and destination of the transportation task, the type of earthwork and stone, the volume, the deadline, the basic quotation, the acceptance conditions, and the payment terms.

[0010] Preferably, the transportation equipment bidding and matching module specifically comprises: After a transportation task enters the task order pool, the currently idle equipment is extracted through the transportation capacity resource pool. The smart agent of the idle transportation equipment continuously scans the task order pool on the blockchain and selects all executable transportation task lists from the task order pool based on its own transportation capacity information and current location. For each executable transportation task, the intelligent agent uses its built-in cost model to calculate differentiated quotes for different transportation equipment. These differentiated quotes are obtained by considering the base transportation cost, additional transportation cost, and dynamic adjustment factor for different transportation tasks. The intelligent agent calculates the price for each executable transportation task, signs the transportation equipment with its digital signature, and sends it to the edge computing node to participate in task matching.

[0011] Preferably, the intelligent matching module for transportation tasks specifically comprises: The intelligent agent submits a digitally signed quotation data packet to the edge computing node where each executable transportation task is located. The edge computing node then verifies the authenticity and compliance of each received quotation data packet. Edge computing nodes read the clearing and settlement rules data of transportation tasks embedded in blockchain smart contracts, including basic quotes and estimated completion times; Edge computing nodes read the price, promised completion time, and reputation score of the transportation equipment from the price data packet. The market clearing and settlement algorithm with predefined rules is executed. After the edge computing node performs global order matching for all transportation equipment, the optimal transportation equipment is matched and the smart contract is signed to allocate the order. The edge computing node generates a clearing and settlement proof record, sends detailed execution instructions to the optimal transportation equipment after the blockchain smart contract state is updated, and records the task in the blockchain log; Continue processing the order matching process for each transportation task in the task order pool.

[0012] Preferably, the transportation task execution and optimization module specifically comprises: The virtual pheromone map is a shared digital map covering the entire canal waterway construction area, and the virtual pheromone concentration is recorded for each transportation route. By extracting the efficiency pheromone concentration distribution along the path from the current location to the loading point from the virtual pheromone map, the path with the highest concentration is selected as the initial driving route. During the execution of a task, the transportation equipment releases virtual pheromones to its virtual pheromone map coordinates via an intelligent agent through an onboard terminal; During the journey, the intelligent agent collects the efficiency pheromone concentration of alternative routes in real time. If the efficiency pheromone concentration of an alternative route is better than that of the initial route, the intelligent agent immediately switches to that route and displays it on the vehicle terminal of the transportation equipment.

[0013] Preferably, the virtual pheromone concentration includes efficiency pheromone concentration and demand pheromone concentration; Efficiency pheromone concentration is used to characterize the efficiency of a transportation route, and the specific update process is as follows: Based on the designed capacity of the transportation routes, preset the initial efficiency pheromone concentration for different routes; When a transport device travels on a certain path, the actual travel time and resource consumption data of the device on that path are collected in real time. The actual travel time is compared with the standard travel time of that path, and the actual resource consumption is compared with the standard resource consumption of that path. The transport path efficiency is obtained from the two comparison results. The transport path efficiency is converted into efficiency pheromone concentration. The efficiency pheromone concentration of the virtual pheromone map is dynamically updated with low latency through distributed computing nodes. Demand pheromone concentration is used to characterize the urgency of the demand for transportation equipment at the loading and unloading points of the task. The specific update process is as follows: For each task loading point, the current volume of earthwork to be transported and the maximum volume of earthwork to be transported that the loading point can accommodate are obtained. The ratio of the volume of earthwork to be transported to the maximum volume of earthwork to be transported is calculated to obtain the urgency of the loading point's need for transportation equipment. The higher the ratio, the more urgent the need for transportation equipment at the loading point, and the higher the task pheromone concentration at the loading point. The urgency of the need for transportation equipment is converted into task pheromone concentration. Through distributed computing nodes, the task pheromone concentration of the task loading point in the virtual pheromone map is updated dynamically with low latency. For each task unloading point, the remaining acceptable earthwork volume and the maximum receiving capacity of the unloading point are obtained. The ratio of the remaining acceptable earthwork volume to the maximum receiving capacity is calculated to determine the urgency of the unloading point's need for transportation equipment. The higher the ratio, the more urgent the need for transportation equipment at the unloading point, and the higher the task pheromone concentration at the unloading point. The urgency of the need for transportation equipment is converted into task pheromone concentration. Through distributed computing nodes, the task pheromone concentration of the task unloading point in the virtual pheromone map is dynamically updated with low latency.

[0014] Preferably, a method for intelligent scheduling and transportation of earthwork and stone for canal construction includes the following steps: Step S01: The transportation equipment encrypts its transportation capacity information and uploads it to a shared transportation capacity resource pool through the vehicle terminal. The construction party publishes the transportation task to the task order pool in the form of a blockchain smart contract. Step S02: The intelligent agent of the idle transportation equipment continuously scans the task order pool, conducts demand bidding for tasks based on the cost model built into the intelligent agent, and generates differentiated quotations for different transportation equipment for the tasks in the task order pool. Step S03: The market clearing and settlement algorithm running on the edge computing node performs task matching according to the predefined rules of the blockchain smart contract, matches the optimal transportation equipment, and generates a blockchain record; Step S04: During the task execution process, the transportation equipment releases and senses virtual pheromones to the virtual pheromone map where it is located based on the intelligent agent, and performs self-organized path optimization and dynamic updates of the pheromone map.

[0015] The technical effects and advantages of this invention are as follows: 1. This invention provides an intelligent scheduling and transportation method and system for earthwork and stone in canal construction. It constructs a blockchain-based transportation capacity resource pool and task order pool. An intelligent agent for idle transportation equipment continuously scans the task order pool. Based on the cost model built into the intelligent agent, it conducts demand bidding for tasks. Differentiated quotations for different transportation equipment are generated based on the basic transportation cost, additional transportation cost, and dynamic adjustment factors for different transportation tasks. Running on an edge computing node, it reads the clearing and settlement rule data and quotation data of transportation tasks embedded in the blockchain smart contract, executes a predefined market clearing and settlement algorithm, and after the edge computing node performs global order matching for all transportation equipment, it matches the optimal transportation equipment, signs a smart contract to allocate the order, and... Generating a blockchain record, unlike the traditional method of assigning specific tasks to specific transportation equipment, which leads to low work efficiency among construction units, this invention constructs a globally transparent pool of transportation capacity resources and a task order pool. This allows idle transportation capacity to be quickly discovered and utilized from a global perspective. Through a cost model, resources are directed to reasonable and efficient task points, reducing empty runs and waiting times for transportation equipment. Furthermore, by using edge computing nodes to match the optimal transportation equipment, scheduling efficiency is improved. This incentivizes transportation providers and equipment owners to provide better and more efficient services, forming a virtuous cycle. Utilizing each intelligent agent and distributed processing at edge nodes, with blockchain ensuring trust, this invention facilitates a decentralized and highly robust scheduling paradigm for canal and waterway construction projects. 2. This invention provides an intelligent scheduling and transportation method and system for earthwork and stone in canal construction. During task execution, the transportation equipment releases and senses virtual pheromones on its virtual pheromone map based on an intelligent agent. The efficiency pheromone concentration distribution along the path from the current location to the loading point is extracted from the virtual pheromone map, and the path with the highest concentration is selected as the initial driving route. During the journey, the intelligent agent collects the efficiency pheromone concentration of alternative paths in real time and judges the path's accessibility. During task execution, the intelligent agent releases virtual pheromones to the coordinates of its virtual pheromone map via the vehicle-mounted terminal. This system enables dynamic updates to the pheromone map. Through intelligent agents on each transportation device, it releases and senses pheromone concentration, achieving automatic and rapid response to dynamic changes and emergencies. Through a positive feedback mechanism, it automatically discovers and strengthens the optimal path. The more and faster a path is traveled, the stronger its pheromone concentration becomes, thus forming a reinforcement cycle. Relying on the interaction between intelligent agents and the virtual pheromone map, it achieves dynamic optimization of transportation paths, effectively solving the problems of poor dynamic adaptability faced by traditional centralized scheduling models in construction projects. It is suitable for linear engineering scenarios such as canal and waterway construction, which involve large areas, many environmental variables, and poor network conditions. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of an intelligent scheduling and transportation system for earthwork and stone in canal construction according to the present invention.

[0017] Figure 2 This is a flowchart illustrating an intelligent scheduling and transportation method for earthwork and stone in canal construction according to the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 As shown, the present invention provides an intelligent scheduling and transportation system for earthwork and stone in canal and waterway construction, including a resource pool construction module, a transportation equipment bidding generation module, a transportation task intelligent matching module, and a transportation task execution and optimization module.

[0020] The resource pool construction module is connected to the transportation equipment bidding generation module, the transportation equipment bidding generation module is connected to the transportation task intelligent matching module, and the transportation task intelligent matching module is connected to the transportation task execution and optimization module.

[0021] The resource pool construction module: The transportation equipment uploads its transportation capacity information to a shared transportation capacity resource pool through the vehicle terminal after encryption, and the construction party publishes the transportation task to the task order pool in the form of a blockchain smart contract.

[0022] In one possible design, the resource pool construction module specifically comprises: The transportation capacity resource pool stores transportation capacity information including the real-time location, load status, load capacity, equipment type, affiliated unit, and reputation value of transportation equipment. All information is encrypted and uploaded to the blockchain network to ensure that the data is tamper-proof and traceable. The blockchain smart contract defines the origin and destination of the transportation task, the type of earthwork and stone, the volume, the deadline, the basic quotation, the acceptance conditions, and the payment terms.

[0023] The transportation equipment bidding generation module: The intelligent agent of idle transportation equipment continuously scans the task order pool, conducts demand bidding for tasks based on the cost model built into the intelligent agent, and generates differentiated quotations for different transportation equipment for tasks in the task order pool.

[0024] In one possible design, the transportation equipment bidding and matching module specifically comprises: After a transportation task enters the task order pool, the currently idle equipment is extracted through the transportation capacity resource pool. The smart agent of the idle transportation equipment continuously scans the task order pool on the blockchain and selects all executable transportation task lists from the task order pool based on its own transportation capacity information and current location. For each executable transportation task, the intelligent agent uses its built-in cost model to calculate differentiated quotes for different transportation equipment. These differentiated quotes are obtained by considering the base transportation cost, additional transportation cost, and dynamic adjustment factor for different transportation tasks. The intelligent agent calculates the price for each executable transportation task, signs the transportation equipment with its digital signature, and sends it to the edge computing node to participate in task matching.

[0025] In this embodiment, it should be specifically noted that the cost model is as follows: The basic transportation costs are as follows: For each executable transportation task, the intelligent agent obtains the empty travel distance from the current location of the equipment to the task loading point through the route planning interface. The heavy-load distance specified in the task from the loading point to the unloading point Average fuel cost of equipment ; For each feasible transportation task, calculate its basic transportation cost:

[0026] in, Let represent the basic transportation cost of the i-th executable transportation task. Let represent the empty travel distance from the current location of the equipment for the i-th executable transportation task to the task loading point. Let represent the heavy-load distance from the loading point to the unloading point as specified in the task definition for the i-th executable transportation task. Let be the average fuel cost of the equipment for the i-th executable transportation task; The additional transportation costs are as follows: For each executable transportation task, the intelligent agent obtains the estimated total queuing time at the loading and unloading points of that task by measuring the throughput of the edge nodes. The opportunity cost per hour of transportation equipment can be obtained by comparing its average daily gross profit with its average daily working hours. (Queuing means losing time to take on other tasks), obtain the preset channel condition difficulty factor through the path planning interface. ; For each feasible transportation task, calculate its additional transportation cost:

[0027] in, Let represent the additional transportation cost for the i-th executable transportation task. Let represent the estimated total queuing time at the loading and unloading points for the i-th executable transport task. Let $\frac{i}{i}$ be the opportunity cost per hour for the equipment performing the $i$-th feasible transportation task. This represents the preset waterway condition difficulty factor for the i-th executable transportation task; As an explanation: The difficulty factor of waterway working conditions can be set according to the impact of hydrological conditions and waterway conditions on transportation during canal construction. The dynamic adjustment factor is as follows: The intelligent agent obtains the current idle time of the transportation equipment. Acceptable maximum idle time Calculate the urgency of device idle time: Specifically, the closer this value is to 1, the stronger the willingness of the device to accept orders; For each executable transportation task, the intelligent agent obtains the number of devices currently quoting a price for that task. Total number of executable tasks Calculate market competitiveness: Specifically, a value less than 1 indicates that the current transportation task is highly competitive, while a value less than 1 indicates that the current transportation task is not highly competitive. The intelligent agent obtains the number of task executions for the current path of the device. Number of complete equipment tasks Calculate path familiarity: Specifically, the more times a device has recently completed a task along the current path, the higher its path familiarity, which means higher efficiency and lower risk in executing the task. Conversely, the fewer times a device has completed a task along the current path, the lower its path familiarity, which means higher risk in executing the task. For each executable transportation task, extract its equipment idle urgency, market competitiveness, and route familiarity, and calculate the dynamic adjustment factor:

[0028] in, It represents the dynamic adjustment factor for the i-th executable transportation task; For each feasible transportation task, a quote is calculated based on the base transportation cost, additional transportation costs, and a dynamic adjustment factor:

[0029] in, This represents the quote for the i-th executable transportation task.

[0030] The intelligent matching module for transportation tasks: The market clearing and settlement algorithm running on the edge computing node performs task matching according to the predefined rules of the blockchain smart contract, matches the optimal transportation equipment, and generates a blockchain record.

[0031] In one possible design, the intelligent matching module for transportation tasks specifically comprises: The intelligent agent submits a digitally signed quotation data packet to the edge computing node where each executable transportation task is located. The edge computing node then verifies the authenticity and compliance of each received quotation data packet. Edge computing nodes read the clearing and settlement rules data of transportation tasks embedded in blockchain smart contracts, including basic quotes and estimated completion times; Edge computing nodes read the price, promised completion time, and reputation score of the transportation equipment from the price data packet. The market clearing and settlement algorithm with predefined rules is executed. After the edge computing node performs global order matching for all transportation equipment, the optimal transportation equipment is matched and the smart contract is signed to allocate the order. The edge computing node generates a clearing and settlement proof record, sends detailed execution instructions to the optimal transportation equipment after the blockchain smart contract state is updated, and records the task in the blockchain log; Continue processing the order matching process for each transportation task in the task order pool.

[0032] The transportation task execution and optimization module: During the task execution process, the transportation equipment releases and senses virtual pheromones to the virtual pheromone map where it is located based on the intelligent agent, and performs self-organized path optimization and dynamic updates of the pheromone map.

[0033] In one possible design, the transportation task execution and optimization module specifically comprises: The virtual pheromone map is a shared digital map covering the entire canal waterway construction area, and the virtual pheromone concentration is recorded for each transportation route. The virtual pheromone concentration includes efficiency pheromone concentration and demand pheromone concentration; Efficiency pheromone concentration is used to characterize the efficiency of a transportation route, and the specific update process is as follows: Based on the designed capacity of the transportation routes, preset the initial efficiency pheromone concentration for different routes; When a transport device travels on a certain path, the actual travel time and resource consumption data of the device on that path are collected in real time. The actual travel time is compared with the standard travel time of that path, and the actual resource consumption is compared with the standard resource consumption of that path. The transport path efficiency is obtained from the two comparison results. The transport path efficiency is converted into efficiency pheromone concentration. The efficiency pheromone concentration of the virtual pheromone map is dynamically updated with low latency through distributed computing nodes. Demand pheromone concentration is used to characterize the urgency of the demand for transportation equipment at the loading and unloading points of the task. The specific update process is as follows: For each task loading point, the current volume of earthwork to be transported and the maximum volume of earthwork to be transported that the loading point can accommodate are obtained. The ratio of the volume of earthwork to be transported to the maximum volume of earthwork to be transported is calculated to obtain the urgency of the loading point's need for transportation equipment. The higher the ratio, the more urgent the need for transportation equipment at the loading point, and the higher the task pheromone concentration at the loading point. The urgency of the need for transportation equipment is converted into task pheromone concentration. Through distributed computing nodes, the task pheromone concentration of the task loading point in the virtual pheromone map is updated dynamically with low latency. For each task unloading point, the remaining amount of earth that can be received and the maximum receiving capacity of the unloading point are obtained. The ratio of the remaining amount of earth that can be received to the maximum receiving capacity is calculated to obtain the urgency of the unloading point's need for transportation equipment. The higher the ratio, the more urgent the need for transportation equipment at the unloading point, and the higher the task pheromone concentration at the unloading point. The urgency of the need for transportation equipment is converted into task pheromone concentration. Through distributed computing nodes, the task pheromone concentration of the task unloading point in the virtual pheromone map is updated dynamically with low latency. By extracting the efficiency pheromone concentration distribution along the path from the current location to the loading point from the virtual pheromone map, the path with the highest concentration is selected as the initial driving route. During the execution of a task, the transportation equipment releases virtual pheromones to its virtual pheromone map coordinates via an intelligent agent through an onboard terminal; During the journey, the intelligent agent collects the efficiency pheromone concentration of alternative routes in real time. If the efficiency pheromone concentration of an alternative route is better than that of the initial route, the intelligent agent immediately switches to that route and displays it on the vehicle terminal of the transportation equipment.

[0034] In this embodiment, it should be specifically noted that when the transportation equipment is idle, the intelligent agent selects the area with the highest concentration of demand pheromones from the virtual pheromone map, attracts idle equipment to perform tasks, and improves task allocation efficiency.

[0035] Please see Figure 2As shown, this invention provides an intelligent scheduling and transportation method for earthwork and stone in canal construction, comprising the following steps: Step S01: The transportation equipment encrypts its transportation capacity information and uploads it to a shared transportation capacity resource pool through the vehicle terminal. The construction party publishes the transportation task to the task order pool in the form of a blockchain smart contract. Step S02: The intelligent agent of the idle transportation equipment continuously scans the task order pool, conducts demand bidding for tasks based on the cost model built into the intelligent agent, and generates differentiated quotations for different transportation equipment for the tasks in the task order pool. Step S03: The market clearing and settlement algorithm running on the edge computing node performs task matching according to the predefined rules of the blockchain smart contract, matches the optimal transportation equipment, and generates a blockchain record; Step S04: During the task execution process, the transportation equipment releases and senses virtual pheromones to the virtual pheromone map where it is located based on the intelligent agent, and performs self-organized path optimization and dynamic updates of the pheromone map.

[0036] In this embodiment, it should be specifically explained that the present invention constructs a blockchain-based capacity resource pool and task order pool. An intelligent agent for idle transportation equipment continuously scans the task order pool and conducts demand bidding for tasks based on the built-in cost model of the intelligent agent. Differentiated quotations for different transportation equipment are generated by considering the basic transportation cost, additional transportation cost, and dynamic adjustment factors for different transportation tasks. Running on an edge computing node, the system reads the clearing and settlement rule data of transportation tasks embedded in the blockchain smart contract, executes a predefined market clearing and settlement algorithm, and after the edge computing node performs global order matching for all transportation equipment, it matches the optimal transportation equipment, signs the smart contract to allocate the order, and generates a blockchain record. Unlike traditional methods that assign specific tasks to specific transportation equipment, resulting in low efficiency for each construction unit, this invention constructs a globally transparent pool of transportation capacity resources and a task order pool. This allows idle transportation capacity to be quickly discovered and utilized from a global perspective. Through a cost model, resources are directed to reasonable and efficient task points, reducing empty runs and waiting times for transportation equipment. Furthermore, by using edge computing nodes to match the optimal transportation equipment, scheduling efficiency is improved. This incentivizes transportation providers and equipment owners to provide higher-quality and more efficient services, creating a virtuous cycle. Utilizing each intelligent agent and distributed processing at edge nodes, with blockchain ensuring trust, this invention facilitates a decentralized and highly robust scheduling paradigm for canal and waterway construction projects. This invention utilizes intelligent agents to release and sense virtual pheromones on a virtual pheromone map during the execution of a transportation device's mission. The map extracts the efficiency pheromone concentration distribution along the path from the current location to the loading point, selecting the path with the highest concentration as the initial route. During travel, the intelligent agent continuously collects the efficiency pheromone concentration of alternative paths and assesses path accessibility. The intelligent agent releases virtual pheromones from the vehicle's onboard terminal to the virtual pheromone map coordinates, enabling dynamic updates to the pheromone map. By releasing and sensing pheromone concentrations through the intelligent agent of each transportation device, it achieves automatic and rapid response to dynamic changes and unexpected events. A positive feedback mechanism automatically discovers and strengthens the optimal path; the more and faster a path is traveled, the stronger its pheromone concentration becomes, forming a reinforcement cycle. Through the interaction between the intelligent agent and the virtual pheromone map, dynamic optimization of transportation paths is achieved. This effectively solves the problems of poor dynamic adaptability faced by traditional centralized scheduling models in construction projects, making it suitable for linear engineering scenarios such as canal and waterway construction, which involve large areas, numerous environmental variables, and poor network conditions.

[0037] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A canal channel construction earthwork stone intelligent scheduling and transportation system, characterized in that, The application relates to a resource pool construction module, a transport equipment competitive generation module, a transport task intelligent matching module and a transport task execution and optimization module. The resource pool construction module is specifically characterized in that: The transport capacity resource pool stores transport capacity information including real-time positions, load states, load capacities, device types, units and credit values of the transport equipment, and all the information is uploaded to a blockchain network after being encrypted to ensure that the data cannot be tampered with and is traceable; the blockchain smart contract defines the starting and ending points of a transport task, earthwork types, volume, deadline, basic price, acceptance conditions and payment terms. The transport equipment competitive generation module is specifically characterized in that: After a transport task enters a task order pool, the current idle equipment is extracted from a transport capacity resource pool, the intelligent agent of the idle transport equipment continuously scans the task order pool on the blockchain, and all executable transport task lists are filtered from the task order pool according to the transport capacity information and the current position of the intelligent agent; 2. The intelligent dispatching and transportation system for earthwork stone of canal channel construction according to claim 1, characterized in that: For each executable transport task, the intelligent agent calculates the differential price of different transport equipment by using the built-in cost model, and the differential price is obtained through the basic transport cost, additional transport cost and dynamic adjustment factor of different transport tasks; The intelligent agent sends the price of each executable transport task calculated to an edge computing node to participate in task matching after signing the digital signature of the transport equipment.

3. The intelligent dispatching and transportation system for earthwork stone of canal channel construction according to claim 1, characterized in that: The transport task intelligent matching module is specifically characterized in that: The intelligent agent submits the signed price data packet to the edge computing node of each executable transport task, and the edge computing node verifies the identity authenticity and compliance of each received price data packet; The edge computing node reads the clearing and settlement rule data of the transport task embedded in the blockchain smart contract, including the basic price and the expected completion time; The edge computing node reads the price, promised completion time and credit value of the transport equipment in the price data packet; 4. The intelligent dispatching and transportation system for earthwork stone of canal channel construction according to claim 1, characterized in that: After the edge computing node performs the market clearing and settlement algorithm according to the pre-defined rules, the optimal transport equipment is matched, the smart contract is signed and the order is distributed; The edge computing node generates a clearing and settlement proof record, and after the state of the blockchain smart contract is updated, sends detailed execution instructions to the optimal transport equipment and records the task in the blockchain log. ​ ​ ​ ​ Continue to process the order matching process of each transportation task in the task order pool.

5. The intelligent dispatching and transportation system for earthwork stone of canal channel construction according to claim 1, characterized in that: The transportation task execution and optimization module specifically comprises: The virtual pheromone map is a shared digital map covering the entire canal construction area, and each transportation path records the virtual pheromone concentration; Through the virtual pheromone map, the efficiency pheromone concentration distribution on the path from the current position to the loading point is extracted, and the path with the highest concentration is selected as the initial driving route; During the execution of the task, the intelligent agent releases virtual pheromones in the virtual pheromone map coordinates of the transportation device through the vehicle terminal; During driving, the intelligent agent collects the efficiency pheromone concentration of the alternative path in real time, and if the efficiency pheromone concentration of a certain alternative path is better than that of the initial driving route, the intelligent agent immediately switches to that path and displays it on the vehicle terminal of the transportation device.

6. The intelligent dispatching and transportation system for earthwork stone of canal channel construction according to claim 5, characterized in that: The virtual pheromone concentration includes efficiency pheromone concentration and demand pheromone concentration; The efficiency pheromone concentration is used to represent the efficiency of the transportation path, and the specific updating process is as follows: According to the designed traffic capacity of the transportation path, the initial efficiency pheromone concentration is preset for different paths; When the transportation device is driving on a certain path, the actual driving time and resource consumption data of the device on the path are collected in real time, the actual driving time is compared with the standard driving time of the path, the actual resource consumption is compared with the standard resource consumption of the path, the transportation path efficiency is obtained through the two comparison results, the transportation path efficiency is converted into efficiency pheromone concentration, and the efficiency pheromone concentration of the virtual pheromone map is dynamically updated by the distributed computing node with low delay; The demand pheromone concentration is used to represent the demand urgency of the task loading point and unloading point for the transportation device, and the specific updating process is as follows: For the task loading point, the current amount of earthwork to be transported and the maximum amount of earthwork that can be accommodated by the loading point are obtained, the ratio of the amount of earthwork to be transported to the maximum amount of earthwork to be transported is calculated, and the demand urgency of the loading point for the transportation device is obtained. The higher the ratio, the more urgent the demand of the loading point for the transportation device, and the higher the task pheromone concentration of the loading point. The demand urgency of the transportation device is converted into task pheromone concentration, and the task pheromone concentration of the task loading point in the virtual pheromone map is dynamically updated by the distributed computing node with low delay. For the task unloading point, the remaining receivable earthwork amount and the maximum receiving capacity of the unloading point are obtained, the ratio of the remaining receivable earthwork amount to the maximum receiving capacity is calculated, and the demand urgency of the unloading point for the transportation device is obtained. The higher the ratio, the more urgent the demand of the unloading point for the transportation device, and the higher the task pheromone concentration of the unloading point. The demand urgency of the transportation device is converted into task pheromone concentration, and the task pheromone concentration of the task unloading point in the virtual pheromone map is dynamically updated by the distributed computing node with low delay.

7. A method for intelligent scheduling and transportation of earthwork stones for canal channel construction, using an intelligent scheduling and transportation system for earthwork stones for canal channel construction according to any one of claims 1-6, characterized in that: The following steps are included: Step S01: The transportation device uploads its transport capacity information to a shared transport capacity resource pool through the vehicle terminal after encryption, and the construction party publishes the transportation task to the task order pool in the form of a blockchain smart contract; Step S02: The intelligent agent of the idle transportation device continuously scans the task order pool, and conducts demand bidding for the task based on the cost model built in the intelligent agent, and generates differentiated quotes for different transportation devices for the tasks in the task order pool; Step S03: The market clearing and settlement algorithm running on the edge computing node matches the tasks according to the pre-defined rules of the blockchain smart contract, matches the optimal transportation device, and generates a blockchain record; Step S04: During the task execution process, the transportation device releases and senses virtual pheromones to the virtual pheromone map based on the intelligent agent, and performs self-organizing path optimization and dynamic updating of the pheromone map.

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