211 results about "Resource coordination" patented technology

A system for multi-stage planning of construction processes and resource allocation, consisting of: a central planning engine configured to receive input data, including architectural design models, structural constraints, procurement schedules, and historical performance indicators; a task decomposition processor that is operationally connected to the central planning engine and configured to generate a hierarchical construction task graph by decomposing macro-level construction milestones into mid-level and micro-level subtasks, with each subtask having time estimates, location identifiers, resource requirements, and mutual dependencies; a hybrid planning processing unit configured to resolve time and resource constraints across the entire task diagram; a resource coordination controller that is operationally connected to the central planning engine, wherein the resource coordination controller includes a real-time database of work units, machines and material stocks, each resource being tagged with attributes such as availability, usage history, operating status and spatial location; a multitude of distributed execution units distributed across the construction zones, each distributed execution unit comprising an embedded controller, sensor interfaces, task status processing logic, and communication circuitry, each distributed execution unit being configured to receive planning instructions from the central planning machine, execute localized control logic for task confirmation and resource activation, and transmit task execution data back to the central planning machine; an adaptive conflict resolution processing unit that is operationally connected to the central planning engine and configured to detect conflicts in task execution or resource conflicts, simulate alternative task-resource allocation scenarios using a real-time multi-agent model, and autonomously update the task graph with revised task sequences and resource allocations; and A dashboard for the construction process, configured to visualize task progress, deviations from the planned schedule, and resource efficiency metrics, with the dashboard also being able to receive manual override inputs or approve automated conflict resolution proposals generated by the adaptive conflict resolution module.

The invention discloses a real-time computing system resource coordination and decision engine system based on a large language model. According to the system, a large language model is innovatively used as a central strategic decision engine, and a'decision-coordination-execution 'three-layer architecture is constructed. According to the system, macroscopic strategy generation and microscopic real-time control are decoupled by introducing a hierarchical decision-making mechanism (a strategic layer, a tactical layer and an execution layer), so that the core contradiction between LLM high reasoning delay and the microsecond / millisecond-level real-time requirement of the system is effectively solved, and the method is suitable for local computing equipment and a cloud data center. The system comprises a predictive strategy preloading system, and transient response can be achieved. Meanwhile, the system adopts an asynchronous event-driven decision-making mechanism for continuous intelligent optimization. According to the method, the top-down, semantic understanding-based and global collaborative intelligent management of the computing resources is realized, and the resource utilization efficiency, the system automation degree and the overall energy efficiency in a complex and dynamic computing environment are remarkably improved.

The invention discloses a virtual power plant global optimization scheduling method, system and device based on cloud edge collaboration, and a storage medium, and belongs to the technical field of power system scheduling. The method comprises the following steps: based on a cloud edge coordinated regulation and control framework comprising a cloud layer, an edge layer and an end side layer, taking minimization of the total operation cost of a system as a target, comprehensively considering a power balance constraint, a main network interaction constraint, a distribution network transmission constraint, a distributed resource operation constraint, an energy storage equipment constraint and a renewable energy consumption constraint; establishing a global optimization scheduling model; edge collaborative optimization is realized by adopting an alternating direction multiplier method, a global coupling problem is decomposed into local optimization sub-problems and a cloud coordination problem of each region, and aggregation power information is sent to the cloud after the local optimization sub-problems are solved in parallel in each region; and the cloud performs global coordination optimization to generate an optimal scheduling strategy, and issues a scheduling instruction to the edge layer to control the actual operation of the distributed power supply, the energy storage equipment and the controllable load, thereby realizing the collaborative optimization scheduling of the virtual power plant. The problems that in virtual power plant large-scale distributed resource coordination optimization, calculation complexity is high, communication burden is heavy, and real-time performance and global optimality are difficult to consider at the same time are effectively solved.

The invention relates to a priority scheduling generation method and system for Beidou satellite short message communication, and the method comprises the steps: collecting multi-dimensional features, such as message service types, user identities, spatio-temporal information, channel states and the like, dynamically calculating the priority score of each message through a configurable weighting model, and then, carrying out the dynamic calculation of the priority score of each message; the method comprises the following steps of: abstracting a message into a conflict graph vertex, establishing an edge according to a receiving conflict relationship, distributing candidate message sets which are not conflicted with each other for each scheduling time slot by adopting an independent set selection algorithm, and performing joint optimization on a message sending sequence and power distribution by using a genetic algorithm in each time slot by taking a maximized comprehensive utility value as a target, and generating a final scheduling instruction. Through dynamic evaluation, conflict avoidance and resource collaboration, intelligence and self-adaption of a scheduling strategy are realized, and the guarantee capability of a system for key messages and the overall resource utilization efficiency are remarkably improved.

The invention provides a resource collaborative scheduling system and method for a virtual power plant. The method comprises the following steps: determining space-time probability distribution of wind and light output in the virtual power plant through historical meteorological data and historical illumination data; determining space-time load distribution of an electric vehicle cluster in the virtual power plant, and constructing a source-load interaction scene set under multiple space-time scales in the virtual power plant by fusing the space-time probability distribution and the space-time load distribution; determining a multi-objective optimization function of the virtual power plant according to the price demand signal of the electric energy service market and the source-load interaction scene set; and performing optimization solution on the multi-objective optimization function to obtain a collaborative scheduling plan of the virtual power plant, decomposing the collaborative scheduling plan into a control instruction sequence, and issuing the control instruction sequence to a local controller of each distributed resource. According to the scheme of the invention, a multi-target optimization system considering the operation benefit and the renewable energy power abandonment rate can be constructed through the source-load interaction scene under multiple spatial-temporal scales, so that the closed-loop management and control of the resource scheduling of the virtual power plant can be realized.

The invention discloses a micro-grid automatic power regulation and control method, and relates to the technical field of micro-grid power regulation and control and resource management. In order to solve the defects of poor new energy consumption capability, high distributed resource management difficulty, poor power grid regulation and control flexibility, poor resource cooperation effect and poor power and load prediction accuracy of an existing micro-grid power regulation and control method, grid-connected and off-grid flexible switching of a power grid A and a power grid B is realized by constructing an integrated construction framework. And multi-source data are integrated, and new energy power generation and load demands are intelligently predicted through data center management. And during grid connection, the distribution and dispatching integrated system determines power dispatching, and the micro-grid management system B makes a dispatching plan. And during off-grid, power is supplied according to the user priority. And in the grid-connected and off-grid mode, power distribution, load regulation and control and resource optimization configuration are carried out, and distributed resources are regulated and controlled in real time through the coordination controller, so that stable operation of the power grid is ensured. The method is mainly used for flexibly regulating and controlling the micro-grid.

The invention discloses a multi-objective optimization-based enterprise resource coordination and distribution method, which comprises the following steps of: S1, acquiring multi-dimensional description information of enterprise task requirements, and constructing a requirement diagram; s2, based on the demand graph structure, performing clustering division on task nodes by adopting a self-organizing clustering algorithm, generating task clusters, generating a candidate resource demand set, and constructing a resource node set; s3, constructing a resource scheduling candidate topological graph; s4, defining a scheduling adaptability function containing a multi-target index, wherein the multi-target index comprises cost, period, resource utilization rate and resource scheduling distance; s5, extracting an optimal scheduling sub-graph from the candidate scheduling topology by adopting an improved heuristic aggregation algorithm; and S6, outputting a corresponding resource allocation scheme to complete resource allocation. According to the method, task structure modeling and multi-target scheduling optimization are fused, the precision and adaptability of resource allocation are improved, and the method is suitable for an enterprise resource management system in a complex scheduling scene.

The invention discloses a multi-agent asynchronous collaboration method and system under a centralized architecture, and is suitable for task scheduling and resource coordination of heterogeneous agents in an intelligent Internet of Things environment. According to the method, a main scheduling node centralized control mechanism is adopted, a scheduling priority function is calculated in combination with a multi-agent game model according to real-time state information of a plurality of heterogeneous agents, and asynchronous allocation and feedback control of tasks are achieved. Meanwhile, an asynchronous and synchronous window mechanism is introduced, the scheduling continuity and efficiency can still be kept under the condition of incomplete information, and fairness and robustness of task distribution are achieved through agent feedback delay modeling and revenue function design. The system throughput and the response speed are improved, the isomerism and the expandability are considered, and the method is suitable for multi-agent cooperation scenes such as disaster emergency, industrial manufacturing, smart home and intelligent traffic.

The invention discloses a method and a system for cooperatively controlling post-disaster recovery and multi-source resource coordination of three networks, and belongs to the technical field of post-disaster recovery and toughness improvement of a multi-infrastructure system. The method comprises the following steps: obtaining a node importance evaluation function through multi-index fusion, and calculating a recovery priority score of a grey starting power supply; estimating the node state probability to obtain the node state probability; setting boundary conditions of recovery feasibility of the subarea power grid; optimizing a recovery sequence through a grey starting power supply-load-net rack path matching model, and generating a recovery path set; a reinforcement learning algorithm is adopted, node states, resource availability and a path connection matrix are used as state spaces, and an optimal recovery sequence and a resource scheduling scheme are output; and generating a three-network recovery path recommendation, a partition power grid recovery strategy and a multi-element flexible resource scheduling sequence. According to the invention, efficient scheduling and cross-network cooperative control of multi-source flexible resources are realized, and the recovery efficiency and toughness of three networks in a post-disaster scene are effectively improved.

The invention discloses a U.2 interface-based server intelligent integrated hierarchical storage system and method, relates to the technical field of computer server storage, and is used for solving the problem of optimization of multi-type SSD data access efficiency and storage resource utilization rate. Firstly, a multi-protocol parallel channel is established by redefining U.2 interface reserved pins, signal integrity parameters are monitored in real time and fused with equipment I / O access features, and an I / O feature sequence of physical layer state information is generated; then, based on a time sequence convolutional neural network, extracting access mode multi-scale features, calculating a data block access heat probability, mapping and determining a target storage hierarchy, and generating a scheduling instruction containing a source physical address, the target hierarchy and a migration priority; the migration execution module realizes zero-copy migration of the data block between the shared DRAM pool and the SSD according to the instruction; and the resource coordination module monitors system load in real time, dynamically adjusts migration concurrency and an I / O sampling strategy, and realizes self-adaptive optimization of storage performance and resource utilization.

The invention discloses a multi-resource coordination control method and system in a new energy high-proportion power grid, and the method comprises the steps: collecting power grid data which comprises new energy output data, meteorological data, power grid load data, power grid operation state data and energy storage system operation parameters; constructing a new energy output prediction model based on the power grid data; calculating quantitative cost based on the power grid data and the new energy output prediction model, wherein the quantitative cost comprises energy storage system cost, power grid operation cost and power grid stability cost; constructing an energy storage charging and discharging strategy model based on the quantitative cost; obtaining an optimal energy storage charging and discharging strategy based on the energy storage charging and discharging strategy model; and constructing a multi-resource cooperative scheduling model based on the optimal energy storage charging and discharging strategy, and outputting a scheduling plan. According to the method, the energy storage depreciation, the power grid loss and the stability risk are quantified into specific cost indexes by calculating the quantitative cost, hidden loss can be avoided, and the operation cost of the system is minimized.

The invention relates to the technical field of front-end application development, in particular to a micro-front-end architecture-oriented cross-application state management, style isolation and resource collaborative loading method, which comprises the following steps of: constructing a state management module, establishing a unified state communication protocol based on a publishing / subscribing mode, and realizing safe state synchronization through an authority control mechanism; a style isolation module is constructed, a Shadow DOM and CSS rule rewriting double isolation strategy is adopted, dynamic style elements are automatically processed, and the problem of style pollution is thoroughly solved; constructing a resource coordinator module, and realizing dependent intelligent management and multi-version coexistence based on semantic version specifications; and the configuration management center uniformly coordinates the work of each module. According to the method, safe communication, reliable isolation and efficient resource utilization between micro front-end sub-applications are realized, three core problems of difficult state management, pattern conflict and resource redundancy in the prior art are solved, and the maintainability, the stability and the development efficiency of a large front-end project are remarkably improved.

The invention discloses a coordination control method, system and device for distributed resources of a power distribution network and a medium. The method comprises the steps of obtaining a topological structure, electrical characteristics and resource distribution conditions of the power distribution network; dividing the power distribution network into a plurality of control regions by adopting a self-adaptive partitioning algorithm to obtain a self-adaptive partitioning result; based on the self-adaptive partitioning result, a hierarchical control framework is constructed; different types of distributed resources in the power distribution network are coordinated and optimized through an intra-region resource coordination control algorithm and an inter-region coordination mechanism; and obtaining an optimal power distribution network distributed resource coordination control strategy through a distributed optimization algorithm and a self-adaptive control strategy. Effective control technical support is provided for friendly access of large-scale distributed resources to the power distribution network, and the method has important practical value for improving the bearing capacity of the power distribution network and optimizing the resource utilization efficiency.

The invention provides a networking scene-oriented multipath service optimization method and system, and relates to the technical field of network scheduling optimization, and the method comprises the steps: obtaining topological structure information and service demand information of a communication network in a networking scene, and employing a depth-first search algorithm in combination with a pruning mechanism to generate a candidate path set; on the basis of a marginal value contribution degree theory, calculating a transmission value factor and a path complementary factor of each candidate path in the candidate path set, calculating marginal value contribution degrees of different candidate path combinations according to the two factors, and taking the path combination with the highest marginal value contribution degree as an optimal path combination; and aiming at each path in the optimal path combination, establishing a multi-objective optimization model, and obtaining a final scheduling scheme of the service flow among the paths in the optimal path combination. According to the invention, the problems of lack of differentiated path selection mechanism, poor fault tolerance of single-path transmission, insufficient resource coordination capability and the like in multi-service transmission in the prior art can be solved.

The invention relates to a power distribution network reactive power resource coordination configuration method and device, equipment, a medium and a product. The method comprises the following steps: carrying out quantitative evaluation on the utilization rate of the reactive compensation equipment of the power distribution network according to preset indexes to obtain an evaluation value of each preset index; for evaluation objects of different types of power distribution networks, based on a power distribution network reactive power compensation equipment utilization rate grading evaluation index system of an improved radar map method, evaluating the evaluation value of each preset index, and obtaining a reactive power compensation equipment utilization rate comprehensive evaluation result of each evaluation object; constructing a distribution network reactive power compensation equipment configuration optimization model according to the reactive power compensation equipment utilization rate comprehensive evaluation result of each evaluation object; and aiming at different severe scenes, according to each constraint condition in the distribution network reactive power compensation equipment configuration optimization model, determining a distribution network two-stage reactive power collaborative optimization scheduling strategy. Therefore, the voltage quality of the power distribution network under the power conversion single supply working condition is improved, and the reactive equipment utilization rate and the system operation economy are improved.

The invention provides a total element-oriented multi-agent collaborative resource optimization method in an industrial internet, and aims to solve the key problems of difficulty in cross-layer coordination, low scheduling efficiency and the like caused by sensing, decision-making and execution of network work at remarkably different time elements (second level, minute level and hour level) in a multi-networked industrial system. According to the method, an MTPHN (full time element prediction hierarchical network) framework is constructed for a multi-networked industrial system environment with time isomerism, three core modules of feature pyramid prediction, cross-time element synchronization and cooperative scheduling are provided, and effective modeling and vertical-horizontal two-dimensional resource coordination of heterogeneous time streams are realized. According to the method, the production efficiency, the equipment utilization rate and the production value in different operation scenes can be effectively improved, and the method is suitable for dynamic resource scheduling and cross-level collaborative optimization application in a multi-networked industrial system.

The invention discloses a management system for an integrated circuit test, and relates to the technical field of integrated circuit test management, and the system comprises a task scheduling module which is used for receiving a plurality of test task requests, and generating a test task scheduling sequence based on the priority parameter of each test task, the current state of a test resource, and a historical execution result; and the resource coordination module is used for acquiring the running states of the plurality of test devices, executing resource allocation operation according to the test task scheduling sequence, and generating a coordination abnormal event if resource conflict or scheduling failure is detected in the execution process. According to the invention, a dependency graph between test equipment and bottom hardware resources is constructed through the resource coordination module, and accurate modeling of a resource mutual exclusion relationship, concurrent capacity and conflict risk is supported, so that resource conflicts are pre-judged before scheduling, and the problems of resource scrambling and deadlock are effectively avoided.

There is provided a method for resource coordination in a first donor Integrated Access Backhaul (IAB) node connected to a first parent IAB node which is connected to an IAB node, the IAB node further being connected to a second parent IAB node which is connected to a second donor IAB node. The method comprises: sending, to the second donor IAB node, an indication of a first resource configuration for the IAB node, the first resource configuration determined by the first donor IAB node; receiving, from the second donor IAB node, a request for a second resource configuration for the IAB node; and determining a resource configuration for the IAB node based at least on one of the first resource configuration and the second resource configuration.

The invention relates to the technical field of big data network communication, and discloses a big data network communication coordination method and device, and a storage medium. The method comprises the following steps: acquiring original communication data, cleaning and classifying the original communication data, and generating an initial coordination scheme; generating a parallel influence data set based on entropy quantization and a PageRank algorithm; generating a bandwidth demand value through normalization processing and dynamic correction; executing multi-level threshold judgment and selecting a content optimization or data compression strategy; integrating the initial scheme and the correction parameters to carry out strategy fusion and simulation evaluation, and generating a final coordination scheme; and monitoring a resource state through a protocol and generating a feedback optimization parameter. According to the invention, the data processing efficiency and the resource coordination capability of network communication are improved, and the system adaptability and the transmission stability are enhanced.

The invention discloses a power system flexibility resource cooperative scheduling method and device, a terminal and a medium, and relates to the technical field of new energy scheduling. According to the scheme provided by the invention, firstly, energy network structures and flexibility resource parameters in a region are collected, and then clustering is carried out according to resource types and technical parameters; a plurality of resource sets capable of being scheduled in a unified mode are formed, the resource utilization rate is improved through resource integration, distributed energy resources and demand response plans are integrated by constructing a double-layer optimization model, the system flexibility is maximized through an upper-layer model, the operation cost is optimized through a lower-layer model, and various resources are coordinated in combination with an aggregation processing mechanism. And finally, iteratively solving the double-layer model, and finally outputting a scheduling scheme considering both flexibility and economy, so that the problem of insufficient resource collaboration in the prior art is effectively solved, the flexibility and stability of the system are improved, and the adjustment potential of the system is maximized on the premise of ensuring the operation safety.

The invention provides a multi-park-oriented equipment operation and maintenance work order assignment method and a path planning system, and belongs to the technical field of multi-park management. The method comprises the following steps: constructing a digital twinborn model of a'park-building-space-equipment-accessory-operation and maintenance personnel 'six-level topology, splitting an operation and maintenance work order into feature vectors of skill requirements, accessory requirements and energy consumption sensitivity, and generating an initial order dispatching scheme and path planning based on a topological relation and the feature vectors; and the order dispatching scheme and the path planning are dynamically adjusted according to the real-time feedback of the equipment monitoring system in the execution process. According to the method, integrated intelligent decision and dynamic optimization of accessories, personnel, paths and energy consumption are realized, the problems of difficult resource coordination and response delay in multi-park operation and maintenance are effectively solved, and the operation and maintenance efficiency and the resource utilization rate are remarkably improved.

The invention relates to the technical field of power distribution network optimization control, in particular to a power distribution network distributed resource coordination optimization method, system and device based on voltage stability constraint and a storage medium. The method comprises the following steps: firstly, acquiring a power distribution network topological structure and distributed resource characteristic parameters, constructing a voltage sensitivity analysis model, calculating voltage sensitivity indexes of nodes, determining voltage weak nodes and constructing a voltage stability evaluation model; then, a voltage stability margin quantitative model is established in combination with distributed resource operation characteristics, and a multi-target coordination optimization model including voltage deviation minimization, voltage stability margin maximization, distributed resource access capacity maximization and network loss minimization is constructed; solving the optimization model by adopting an improved particle swarm algorithm to obtain a distributed resource optimal configuration scheme; and finally, establishing a dynamic access control strategy to realize adaptive capacity adjustment and reactive power coordination control of distributed resources. The problem of voltage stability in a high-permeability distributed resource access scene is solved.

The invention discloses a resource collaborative and complementary low-carbon configuration method, system and device and a medium, and belongs to the technical field of power system planning, and the method comprises the following steps: building a carbon power market transaction model according to a carbon market transaction mechanism; the method comprises the following steps: establishing a double-layer optimization model of the adjustable resource collaborative complementary configuration by combining the operating characteristics of wind power, photoelectricity, energy storage and thermal power and taking the carbon transaction cost and the carbon quota income of a carbon power market transaction model as constraint conditions through the characteristics of the adjustable resource collaborative complementary configuration; and aiming at the double-layer optimization model, setting a genetic algorithm to solve the double-layer optimization model. According to the invention, by establishing the carbon power market transaction model, the carbon emission cost and the carbon quota income are organically integrated into the power system optimization decision, and deep coupling of economic benefits and environmental benefits is realized.

This invention discloses a method for automatic switching and resource coordination of a system in daily and extreme scenarios, relating to the field of intelligent Internet of Things (IoT) communication technology. Specifically, it includes setting up a probe program at an edge node and initializing its first state to "off," setting up a central node and initializing its first state to "off," collecting data, loading rules to process the data, generating first data and transmitting it to the central node, the central node judging the first data and issuing a state switching command to each edge node, switching the central node's first state to "on," the edge nodes receiving the state switching command switching their first state to "on," loading new preset rules to process the data, generating second data and transmitting it to the central node, the central node obtaining the first and second data from the edge nodes and judging them; if the judgment result meets preset conditions, it issues a device operation command to the edge nodes.

The invention discloses a county isolated network frequency correction control system supported by multiple resources cooperatively, which relates to the technical field of intelligent power grids and comprises a control center, and the control center is connected with a resource acquisition module, a cooperative processing module, a support analysis module and an intelligent correction module. Constructing a power grid comprehensive layout map, collecting power grid composite data, extracting an isolated grid regional frequency to construct a regional frequency dynamic graph, and performing frequency tense judgment on the regional frequency dynamic graph to obtain an isolated grid frequency judgment result; performing frequency measurement updating on the power grid comprehensive layout diagram to obtain an abnormal power grid marking diagram; performing anomaly grading on the abnormal power grid mark graph to obtain a node frequency deviation degree, and performing frequency supplementary rescue on the isolated network block according to the node frequency deviation degree to obtain a dynamic correction scheme; the frequency control capability is improved and the power system stability is enhanced.

The invention discloses a cross-domain PaaS application elastic expansion system, method and device based on a micro-service architecture and a medium, and belongs to the technical field of micro-services, and the system comprises a service registration center, a load state evaluation module, a light load state resource optimization module, an overload state resource optimization module and an execution module. The service registration center is used for receiving the micro-service information and summarizing and storing the micro-service information to form a micro-service list; the load state evaluation module is used for monitoring the index data of the micro-service in the micro-service list, and evaluating the load state of the micro-service according to the index data to obtain a load state evaluation result of the micro-service; the light load state resource optimization module is used for generating a resource recovery decision; the overload state resource optimization module is used for generating a resource extension decision; and the execution module is used for executing the resource recovery decision and the resource extension decision. According to the invention, a cross-domain resource coordination allocation mechanism is combined with service priority arbitration, so that the problem of unreasonable resource allocation is solved.

The invention provides a resource coordination method and device, equipment, a medium and a program product, and aims to solve the problem that the utilization rate of time-frequency resources is relatively low. The method is applied to a resource coordination unit, and comprises the following steps: receiving perception report data sent by a plurality of base stations and demand information sent by platform equipment; and determining resource configuration information based on the work parameter information of the plurality of base stations, the sensing report data and the demand information, the resource configuration information being used for adjusting the configuration of at least one of the time domain resource, the frequency domain resource and the space domain resource of the plurality of base stations. The application can improve the utilization rate of time-frequency resources.

The application relates to the technical field of house renting management, and discloses a long-term house renting monitoring management system and method, which comprises the following steps: dividing monitoring units in the same physical space into equipment groups, recording state jump time stamps, automatically depositing behavior logic templates based on historical time stamp sequences, and generating risk early warnings through logical self-consistency comparison between real-time sequences and templates. The application enables the system to understand the cooperative behavior logic of the equipment, realizes cognitive transition from physical quantity monitoring to behavior logic verification by constructing behavior templates through reuse of basic switch signals, and simultaneously utilizes state credibility evaluation and a distributed priority arbitration mechanism to naturally form an anti-interference data quality firewall and system-level resource coordination capability under a centerless architecture, thereby significantly improving the economy and reliability of intelligent reconstruction of old houses.

The invention discloses a shuttle garage scheduling system, which relates to the field of garage scheduling, and comprises the steps of configuring an equipment object set, solidifying an object identification rule, configuring an object attribute field, setting a topological graph in a garage, defining node edge structure semantics, setting a mutually exclusive resource mapping relationship, setting an RFID addressing and positioning reference, and setting a communication and interface protocol. Through dynamic path planning and a cross-roadway conflict avoidance mechanism, key positions such as cross-roadway rail changing, layer changing entrances, channel convergence and the like are brought into unified mutual exclusion reservation and occupation management, so that the multi-vehicle running process has controllable time sequence alignment and resource coordination capabilities, the risks of vehicle meeting, lane crossing, congestion amplification and deadlock are avoided, and the safety of the system is improved. Meanwhile, in combination with state receipt, anomaly recognition and rescheduling closed loop, the scheduling system triggers task redistribution and path recalculation when equipment occupancy is abnormal and channel congestion occurs, operation continuity and operation stability are kept, and the reliability, safety and long-term availability of the whole system are improved.