Logistics management and control system based on big data

Abstract

The invention discloses a logistics management and control system based on big data, and particularly relates to the technical field of logistics management and control. The intelligent sensing automatic response module is used for controlling various parameters in a transportation environment in real time through a sensor network and the Internet of Things technology, and the virtual augmented reality support module is used for monitoring the states of vehicles and goods in real time through the AR / VR technology. Real-time monitoring and intelligent adjustment are achieved through the sensor network and the Internet of Things technology, and the transportation efficiency and accurate cargo management are improved; real-time monitoring and immersive training are provided in combination with the AR / VR technology, and the operation skill and driving safety are enhanced; data transparency and security are ensured by using the block chain, and whole-course traceability and multi-party data sharing are realized; rapid delivery of last kilometer distribution and automatic warehouse operation are achieved through the unmanned aerial vehicle and robot technology; the system can also simulate and optimize supply chain management, and the overall efficiency and the cooperative capability are improved; and the customer experience is enhanced through the VR customer interaction module.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics management and control, and in particular to a logistics management and control system based on big data. Background Art

[0002] Logistics control system is an important technical means in the modern logistics industry, aiming to improve the efficiency and accuracy of logistics transportation through efficient management and monitoring means. With the rapid growth of global e-commerce and logistics demand, traditional logistics management methods face many challenges, such as difficulty in real-time monitoring, complex cargo management, and low transportation efficiency. In recent years, with the development of advanced technologies such as the Internet of Things, big data, blockchain and drones, intelligent and automated logistics control systems have gradually become a trend in the development of the industry. These technologies provide the logistics industry with more efficient, secure and transparent management means through data collection, analysis and application.

[0003] The existing logistics control system has some defects in practical application. First, the monitoring means of the traditional logistics system are limited, and it is difficult to achieve real-time monitoring and intelligent adjustment of the entire transportation process, resulting in low transportation efficiency and inaccurate cargo management. Secondly, the existing system lacks advanced training and operation skills improvement means, and the skill levels of logistics operators are uneven, which affects the safety and efficiency of logistics operations. In addition, the lack of transparency and security of data management is also a major problem of the traditional logistics system. Data is easily tampered with and leaked, and it is impossible to achieve full traceability and multi-party data sharing. Furthermore, the traditional logistics system relies on manual labor in the last mile distribution and warehouse operations, which is inefficient and costly, and it is difficult to meet the needs of fast delivery and automated operations. Finally, the supply chain management capabilities of the existing system are limited, and it is impossible to improve the overall efficiency and coordination capabilities through simulation and optimization. The customer experience is also relatively simple, lacking interactivity and immersion. Therefore, a logistics control system based on big data is needed. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a logistics management and control system based on big data.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A logistics control system based on big data, including an intelligent perception automatic response module for real-time control of various parameters in the transportation environment through sensor networks and Internet of Things technology, a virtual augmented reality support module for real-time monitoring of vehicle and cargo status using AR / VR technology, a blockchain and smart contract module for ensuring data immutability and transparency using blockchain technology, and a drone-robot collaboration module for fast delivery in the last mile of distribution by combining drone and robot technology;

[0007] The intelligent perception automatic response module includes an adaptive environmental perception module for perceiving temperature, humidity, and vibration parameters in the transportation environment through sensor networks and Internet of Things technologies, a dynamic road condition adjustment module for automatically adjusting the transportation route based on real-time traffic data and predictive analysis, an autonomous driving support module for supporting the dispatching and monitoring of autonomous driving freight vehicles in combination with L4 level autonomous driving technology, and an intelligent cargo identification module for automatically identifying and classifying cargo using RFID and image recognition technologies;

[0008] The virtual augmented reality support module includes an AR real-time monitoring module for enabling cargo owners and managers to view the status of transport vehicles and cargoes in real time through augmented reality technology, a VR simulation training module for providing immersive training for drivers and warehouse managers using virtual reality technology, an AR navigation assistance module for adding augmented reality functions to the driver's navigation system, and a VR logistics planning module for simulating different logistics solutions through virtual reality technology;

[0009] The blockchain and smart contract module includes a transparent transportation chain module for recording the whole process information of goods from shipment to receipt by using blockchain technology, a smart transportation contract module for automatically executing transportation agreements through smart contracts, a blockchain traceability module for achieving full traceability of high-value and sensitive goods, and a decentralized data sharing module for achieving secure multi-party data sharing by using blockchain technology;

[0010] The drone robot collaborative module includes a drone express module for quickly delivering small goods using drones, a warehouse robot module for introducing robots in warehouses for automatic sorting, handling and loading, an unmanned forklift module for realizing automated forklift operation using unmanned driving technology and sensor networks, and an air-ground collaborative distribution module for combining drones and autonomous driving vehicles to realize air-ground integrated collaborative distribution.

[0011] The present invention is further configured as follows: the VR logistics planning module includes a VR environment simulation module for simulating a logistics environment using virtual reality technology to carry out comprehensive warehousing and transportation planning, a VR simulation training module for providing warehousing and transportation operation simulation training through virtual reality technology, a VR logistics path planning module for simulating transportation processes of different logistics paths using VR technology, a logistics demand determination module for planning transportation paths, cargo handling and warehousing accordingly according to different logistics demands (general demands and special demands), a transportation tool determination module for providing targeted simulation and optimization solutions according to selected transportation tools (land transportation tools and sea transportation tools), a VR supply chain management module for simulating the entire supply chain operation process, a VR customer interaction module for providing customers with the function of experiencing the logistics process through VR, and a VR real-time monitoring module for real-time monitoring of the logistics process through VR technology;

[0012] The logistics demand determination module includes general demand and special demand;

[0013] Among them: ordinary needs include a basic route planning module for route planning based on basic needs and an ordinary cargo handling module for simulating the loading, unloading and transportation process of ordinary cargo; special needs include a cold chain logistics planning module for route and warehousing planning for special needs of cold chain logistics and a dangerous goods transportation planning module for simulating the transportation and handling of dangerous goods;

[0014] The transportation tool determination module includes land transportation tools and sea transportation tools;

[0015] Among them: the land transportation tools include an automatic truck simulation module for simulating the operation of self-driving trucks under different road conditions and an ordinary truck simulation module for simulating the operation and maintenance of ordinary trucks; the sea transportation tools include a ship loading and unloading simulation module for simulating the loading and unloading and transportation process of the ship and a sea transportation route planning module for simulating different sea transportation routes through VR.

[0016] The present invention is further configured as follows: the VR simulation training module uses the VR environment simulation module to provide a realistic logistics environment to simulate the warehousing and transportation operations; the VR logistics path planning module uses the real logistics environment created by the VR environment simulation module to simulate the transportation process of different logistics paths; the VR simulation training module uses the path planning solution provided by the VR logistics path planning module to train the path planning ability of operators; the VR logistics path planning module simulates and optimizes the logistics path according to the general demand and special demand data provided by the logistics demand determination module; the VR environment simulation module creates a corresponding simulation environment according to the specific demand determined by the logistics demand determination module; the transportation tool determination module selects the appropriate transportation tool according to the logistics demand type determined by the logistics demand determination module tools and provide simulation and optimization solutions; the VR environment simulation module uses the transportation tools selected by the transportation tool determination module to simulate the operation of these tools in the actual environment; the VR logistics path planning module uses the tool selection provided by the transportation tool determination module to simulate the transportation process of different paths; the VR supply chain management module simulates the operation process of the entire supply chain in the overall supply chain environment provided by the VR environment simulation module; the VR supply chain management module performs comprehensive supply chain planning based on the needs determined by the logistics demand determination module; the VR customer interaction module uses the real-time logistics process data provided by the VR real-time monitoring module to allow customers to experience and monitor the entire logistics process; the VR customer interaction module uses the realistic logistics environment provided by the VR environment simulation module to allow customers to immerse themselves in the logistics process.

[0017] The present invention is further configured as follows: the adaptive environmental perception module automatically adjusts the transportation route using the real-time traffic data provided by the dynamic road condition adjustment module; the autonomous driving support module supports autonomous driving freight vehicle scheduling and monitoring using the transportation environment parameters provided by the adaptive environmental perception module; and the intelligent cargo identification module realizes automatic identification and classification of cargo using the environmental data provided by the adaptive environmental perception module.

[0018] The present invention is further configured as follows: the AR real-time monitoring module uses the training data provided by the VR simulation training module to view the status of transport vehicles and goods in real time; the AR navigation assistance module uses the real-time status data provided by the AR real-time monitoring module to provide navigation assistance for the driver; and the VR logistics planning module uses the training environment provided by the VR simulation training module to simulate different logistics plans.

[0019] The present invention is further configured as follows: the transparent transportation chain module utilizes the intelligent transportation contract module to automatically execute the transportation agreement and record the whole process information of the goods; the blockchain traceability module utilizes the recorded data provided by the transparent transportation chain module to realize the whole process traceability of high-value and sensitive goods; the decentralized data sharing module utilizes the traceability data provided by the blockchain traceability module to realize the secure sharing of multi-party data.

[0020] The present invention is further configured as follows: the drone express module uses the collaborative data provided by the air-ground collaborative distribution module to quickly deliver small goods; the warehouse robot module uses the automated operation data provided by the unmanned forklift module to automatically sort, transport and load in the warehouse; the air-ground collaborative distribution module uses the delivery data provided by the drone express module to realize air-ground integrated collaborative distribution.

[0021] The beneficial effects of the present invention are:

[0022] The present invention realizes real-time monitoring and intelligent adjustment through sensor networks and Internet of Things technologies, thereby improving transportation efficiency and precise cargo management; combines AR / VR technologies to provide real-time monitoring and immersive training, enhancing operational skills and driving safety; uses blockchain to ensure data transparency and security, and realizes full traceability and multi-party data sharing; realizes fast delivery of the last mile of distribution and automated warehouse operations through drone and robot technologies; the system can also simulate and optimize supply chain management, improving overall efficiency and coordination capabilities; and enhances customer experience through VR customer interaction modules. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the system in the present invention.

[0024] Figure 2 This is a partial system diagram of the VR logistics planning module in the present invention. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0026] Example 1

[0027] like Figure 1 As shown, a logistics control system based on big data includes an intelligent perception automatic response module for real-time control of various parameters in the transportation environment through sensor networks and Internet of Things technologies, a virtual augmented reality support module for real-time monitoring of vehicle and cargo status using AR / VR technology, a blockchain and smart contract module for ensuring data immutability and transparency using blockchain technology, and a drone-robot collaboration module for fast delivery in the last mile of distribution by combining drone and robot technologies;

[0028] The intelligent perception automatic response module includes an adaptive environmental perception module for perceiving temperature, humidity, and vibration parameters in the transportation environment through sensor networks and Internet of Things technologies, a dynamic road condition adjustment module for automatically adjusting the transportation route based on real-time traffic data and predictive analysis, an autonomous driving support module for supporting the dispatching and monitoring of autonomous driving freight vehicles in combination with L4 level autonomous driving technology, and an intelligent cargo identification module for automatically identifying and classifying cargo using RFID and image recognition technologies;

[0029] The virtual augmented reality support module includes an AR real-time monitoring module for enabling cargo owners and managers to view the status of transport vehicles and cargoes in real time through augmented reality technology, a VR simulation training module for providing immersive training for drivers and warehouse managers using virtual reality technology, an AR navigation assistance module for adding augmented reality functions to the driver's navigation system, and a VR logistics planning module for simulating different logistics solutions through virtual reality technology;

[0030] The blockchain and smart contract module includes a transparent transportation chain module for recording the whole process information of goods from shipment to receipt by using blockchain technology, a smart transportation contract module for automatically executing transportation agreements through smart contracts, a blockchain traceability module for achieving full traceability of high-value and sensitive goods, and a decentralized data sharing module for achieving secure multi-party data sharing by using blockchain technology;

[0031] The drone robot collaboration module includes a drone express module for using drones to quickly deliver small items, a warehouse robot module for introducing robots in warehouses for automatic sorting, handling and loading, an unmanned forklift module for realizing forklift automation operation using unmanned driving technology and sensor networks, and an air-ground collaborative delivery module for combining drones and autonomous driving vehicles to realize air-ground integrated collaborative delivery;

[0032] The adaptive environment perception module automatically adjusts the transportation route using the real-time traffic data provided by the dynamic road condition adjustment module; the autonomous driving support module supports the dispatching and monitoring of autonomous driving freight vehicles using the transportation environment parameters provided by the adaptive environment perception module; the intelligent cargo identification module realizes automatic identification and classification of cargo using the environmental data provided by the adaptive environment perception module;

[0033] The AR real-time monitoring module uses the training data provided by the VR simulation training module to view the status of transport vehicles and goods in real time; the AR navigation assistance module uses the real-time status data provided by the AR real-time monitoring module to provide navigation assistance for the driver; the VR logistics planning module uses the training environment provided by the VR simulation training module to simulate different logistics solutions;

[0034] The transparent transport chain module uses the intelligent transport contract module to automatically execute the transport agreement and record the whole process information of the goods; the blockchain traceability module uses the recorded data provided by the transparent transport chain module to achieve full traceability of high-value and sensitive goods; the decentralized data sharing module uses the traceability data provided by the blockchain traceability module to achieve secure sharing of multi-party data;

[0035] The drone express module uses the collaborative data provided by the air-ground collaborative distribution module to quickly deliver small goods; the warehouse robot module uses the automated operation data provided by the unmanned forklift module to automatically sort, transport and load in the warehouse; the air-ground collaborative distribution module uses the delivery data provided by the drone express module to achieve integrated air-ground collaborative distribution.

[0036] In the above embodiments, the intelligent perception automatic response module uses sensor networks and Internet of Things technology to control the transportation environment parameters in real time, including temperature, humidity and vibration, and adjusts the transportation route based on real-time traffic data, supports the scheduling and monitoring of autonomous driving freight vehicles, and realizes automatic identification and classification of goods. The virtual augmented reality support module monitors the status of vehicles and goods in real time through AR / VR technology, provides immersive training for drivers and warehouse managers, and provides augmented reality functions in the navigation system to simulate different logistics solutions. The blockchain and smart contract modules ensure that data cannot be tampered with and transparent, and automatically execute transportation agreements through smart contracts to achieve full traceability of goods and secure sharing of multi-party data. The drone robot collaboration module combines drone and robot technology in the last mile of delivery to quickly deliver small goods, and realizes automated operations and air-ground integrated collaborative delivery in the warehouse. Through the collaborative work of these modules, the system can efficiently and safely manage the logistics process, improve transportation efficiency and service quality.

[0037] Among them, the adaptive environmental perception module uses the real-time monitoring data provided by the AR real-time monitoring module to perceive various parameters in the transportation environment; the VR logistics planning module uses the full process information provided by the transparent transportation chain module to simulate different logistics solutions; the unmanned forklift module uses the automatic driving technology support provided by the automatic driving support module to realize the automatic operation of the forklift.

[0038] Example 2

[0039] like Figure 1-2 As shown, a logistics management and control system based on big data, the VR logistics planning module includes a VR environment simulation module for simulating a logistics environment using virtual reality technology for comprehensive warehousing and transportation planning, a VR simulation training module for providing warehousing and transportation operation simulation training through virtual reality technology, a VR logistics path planning module for simulating transportation processes of different logistics paths using VR technology, a logistics demand determination module for planning transportation paths, cargo handling and warehousing according to different logistics needs (general needs and special needs), a transportation tool determination module for providing targeted simulation and optimization solutions according to the selected transportation tools (land transportation tools and sea transportation tools), a VR supply chain management module for simulating the entire supply chain operation process, a VR customer interaction module for providing customers with the function of experiencing the logistics process through VR, and a VR real-time monitoring module for real-time monitoring of the logistics process through VR technology;

[0040] The logistics demand determination module includes general demand and special demand;

[0041] Among them: ordinary needs include a basic route planning module for route planning based on basic needs and an ordinary cargo handling module for simulating the loading, unloading and transportation process of ordinary cargo; special needs include a cold chain logistics planning module for route and warehousing planning for special needs of cold chain logistics and a dangerous goods transportation planning module for simulating the transportation and handling of dangerous goods;

[0042] The transportation tool determination module includes land transportation tools and sea transportation tools;

[0043] Among them: the land transportation tool includes an automatic truck simulation module for simulating the operation of an automatic driving truck under different road conditions and an ordinary truck simulation module for simulating the operation and maintenance of an ordinary truck; the sea transportation tool includes a ship loading and unloading simulation module for simulating the loading and unloading and transportation process of a ship and a sea transportation route planning module for simulating different sea transportation routes through VR;

[0044] The VR simulation training module uses the VR environment simulation module to provide a realistic logistics environment for simulation training of warehousing and transportation operations; the VR logistics path planning module uses the real logistics environment created by the VR environment simulation module to simulate the transportation process of different logistics paths; the VR simulation training module uses the path planning solution provided by the VR logistics path planning module to train the path planning ability of operators; the VR logistics path planning module simulates and optimizes the logistics path according to the general demand and special demand data provided by the logistics demand determination module; the VR environment simulation module creates a corresponding simulation environment according to the specific demand determined by the logistics demand determination module; the transportation tool determination module selects the appropriate transportation tool and provides it according to the logistics demand type determined by the logistics demand determination module Simulation and optimization plan; the VR environment simulation module uses the transportation tools selected by the transportation tool determination module to simulate the operation of these tools in the actual environment; the VR logistics path planning module uses the tool selection provided by the transportation tool determination module to simulate the transportation process of different paths; the VR supply chain management module simulates the operation process of the entire supply chain in the overall supply chain environment provided by the VR environment simulation module; the VR supply chain management module performs comprehensive supply chain planning based on the needs determined by the logistics demand determination module; the VR customer interaction module uses the real-time logistics process data provided by the VR real-time monitoring module to allow customers to experience and monitor the entire logistics process; the VR customer interaction module uses the realistic logistics environment provided by the VR environment simulation module to allow customers to immerse themselves in the logistics process.

[0045] In the above embodiment, first, the VR environment simulation module uses virtual reality technology to create a realistic logistics environment to provide basic support for other modules. The VR simulation training module simulates the warehousing and transportation operations in this environment to improve the skills of operators. The VR logistics path planning module simulates and optimizes the transportation process of the logistics path for different logistics needs (general needs and special needs) in the simulation environment. The logistics demand determination module determines the path planning and cargo handling methods by analyzing different demand data, and then guides the VR logistics path planning module to simulate. The transportation tool determination module selects the appropriate transportation tool according to the demand determination results and provides corresponding simulation and optimization solutions. The VR environment simulation module then uses these tools to simulate its operation in the actual environment. The VR supply chain management module simulates the operation process of the entire supply chain in the overall simulation environment, and comprehensively plans the supply chain according to the results of the demand determination module. The VR customer interaction module provides customer experience and monitoring functions through the real-time logistics data obtained by the VR real-time monitoring module, and uses a realistic logistics environment to allow customers to immerse themselves in the logistics process. Through the collaborative work of these modules, the VR logistics planning module can achieve accurate and efficient logistics planning and management.

[0046] Wherein, the VR path planning module can be planned by using the A* algorithm;

[0047] Definition of Node Each node represents a location in the logistics network. The node contains the following attributes:

[0048] g(n): The actual cost from the starting point to the current node n

[0049] h(n): estimated cost from current node n to the end point (heuristic function)

[0050] f(n): The total estimated cost of node n.

[0051] Parent node: used for path backtracking

[0052] Heuristic Function Choosing a suitable heuristic function is the key to the A* algorithm. For logistics path planning, you can choose Euclidean distance or Manhattan distance as the heuristic function.

[0053] formula:

[0054] Algorithm steps

[0055] Initialize the Open List and the Closed List. Add the starting point to the Open List.

[0056] Repeat the following steps until the end point is found or the open list is empty: a. Select the node with the smallest f(n) from the open list as the current node. b. If the current node is the end point, construct a path and terminate the algorithm. c. Move the current node from the open list to the closed list. d. Perform the following operations on each neighbor of the current node:

[0057] If the neighbor is in the closed list, skip this neighbor.

[0058] Calculate the neighbor's g value (the current node's g value plus the cost from the current node to the neighbor).

[0059] If the neighbor is no longer in the open list, or the new g value is smaller, update the neighbor's g, h, and f values, and set its parent node to the current node. If the neighbor is no longer in the open list, add it to the open list.

[0060] The pseudo code of the VR path planning module is as follows:

[0061]

[0062]

[0063] Working principle: When the present invention is used, first, the sensor network and Internet of Things technology collect transportation environment parameters, and through the intelligent perception automatic response module, real-time control and optimization are carried out, the transportation route is automatically adjusted, the scheduling and monitoring of autonomous driving vehicles are supported, and the automatic identification and classification of goods are realized. The virtual augmented reality support module uses AR / VR technology to monitor the status of vehicles and goods in real time, and provides immersive training and path planning. The logistics demand determination module plans the path, cargo handling and warehousing according to general and special needs, and the transportation tool determination module selects the appropriate transportation tool for simulation. The VR environment simulation module creates a realistic logistics environment and supports the supply chain operation simulation and planning of the VR supply chain management module. The blockchain and smart contract module ensures data transparency and non-tamperability, and realizes full traceability and data sharing. The drone and robot collaboration module combines drone and robot technology for rapid delivery and automated operation in the last mile of distribution. The VR customer interaction module allows customers to experience and monitor the entire logistics process through the real-time logistics data provided by the VR real-time monitoring module. The entire system optimizes path planning through the A* algorithm to achieve accurate and efficient logistics management, improve transportation efficiency and service quality.

[0064] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A logistics management and control system based on big data, characterized in that: It includes an intelligent perception and automatic response module for real-time control of various parameters in the transportation environment through sensor networks and IoT technologies, a virtual augmented reality support module for real-time monitoring of vehicle and cargo status using AR / VR technology, a blockchain and smart contract module for ensuring data immutability and transparency using blockchain technology, and a drone-robot collaboration module for fast delivery in the last mile of delivery by combining drone and robot technologies; The intelligent perception automatic response module includes an adaptive environmental perception module for perceiving temperature, humidity, and vibration parameters in the transportation environment through sensor networks and Internet of Things technologies, a dynamic road condition adjustment module for automatically adjusting the transportation route based on real-time traffic data and predictive analysis, an autonomous driving support module for supporting the dispatching and monitoring of autonomous driving freight vehicles in combination with L4 level autonomous driving technology, and an intelligent cargo identification module for automatically identifying and classifying cargo using RFID and image recognition technologies; The virtual augmented reality support module includes an AR real-time monitoring module for enabling cargo owners and managers to view the status of transport vehicles and cargoes in real time through augmented reality technology, a VR simulation training module for providing immersive training for drivers and warehouse managers using virtual reality technology, an AR navigation assistance module for adding augmented reality functions to the driver's navigation system, and a VR logistics planning module for simulating different logistics solutions through virtual reality technology; The blockchain and smart contract module includes a transparent transportation chain module for recording the whole process information of goods from shipment to receipt by using blockchain technology, a smart transportation contract module for automatically executing transportation agreements through smart contracts, a blockchain traceability module for achieving full traceability of high-value and sensitive goods, and a decentralized data sharing module for achieving secure multi-party data sharing by using blockchain technology; The drone robot collaborative module includes a drone express module for quickly delivering small goods using drones, a warehouse robot module for introducing robots in warehouses for automatic sorting, handling and loading, an unmanned forklift module for realizing automated forklift operation using unmanned driving technology and sensor networks, and an air-ground collaborative distribution module for combining drones and autonomous driving vehicles to realize air-ground integrated collaborative distribution.

2. According to the big data-based logistics management and control system of claim 1, it is characterized in that: The VR logistics planning module includes a VR environment simulation module for simulating the logistics environment using virtual reality technology to carry out comprehensive warehousing and transportation planning, a VR simulation training module for providing warehousing and transportation operation simulation training through virtual reality technology, a VR logistics path planning module for simulating the transportation process of different logistics paths using VR technology, a logistics demand determination module for planning transportation paths, cargo handling and warehousing accordingly according to different logistics needs (general needs and special needs), a transportation tool determination module for providing targeted simulation and optimization solutions according to the selected transportation tools (land transportation tools and sea transportation tools), a VR supply chain management module for simulating the entire supply chain operation process, a VR customer interaction module for providing customers with the function of experiencing the logistics process through VR, and a VR real-time monitoring module for real-time monitoring of the logistics process through VR technology; The logistics demand determination module includes general demand and special demand; Among them: ordinary needs include a basic route planning module for route planning based on basic needs and an ordinary cargo handling module for simulating the loading, unloading and transportation process of ordinary cargo; special needs include a cold chain logistics planning module for route and warehousing planning for special needs of cold chain logistics and a dangerous goods transportation planning module for simulating the transportation and handling of dangerous goods; The transportation tool determination module includes land transportation tools and sea transportation tools; Among them: the land transportation tools include an automatic truck simulation module for simulating the operation of self-driving trucks under different road conditions and an ordinary truck simulation module for simulating the operation and maintenance of ordinary trucks; the sea transportation tools include a ship loading and unloading simulation module for simulating the loading and unloading and transportation process of the ship and a sea transportation route planning module for simulating different sea transportation routes through VR.

3. According to the big data-based logistics management and control system of claim 2, it is characterized in that: The VR simulation training module uses the VR environment simulation module to provide a realistic logistics environment for warehousing and transportation operations simulation training; the VR logistics path planning module uses the real logistics environment created by the VR environment simulation module to simulate the transportation process of different logistics paths; The VR simulation training module uses the path planning solution provided by the VR logistics path planning module to train operators’ path planning capabilities; The VR logistics path planning module simulates and optimizes the logistics path according to the general demand and special demand data provided by the logistics demand determination module; the VR environment simulation module creates a corresponding simulation environment according to the specific demand determined by the logistics demand determination module; the transportation tool determination module selects appropriate transportation tools according to the logistics demand type determined by the logistics demand determination module and provides simulation and optimization solutions; the VR environment simulation module uses the transportation tools selected by the transportation tool determination module to simulate the operation of these tools in the actual environment; the VR logistics path planning module uses the tool selection provided by the transportation tool determination module to simulate the transportation process of different paths; the VR supply chain management module simulates the operation process of the entire supply chain in the overall supply chain environment provided by the VR environment simulation module; the VR supply chain management module performs comprehensive supply chain planning according to the demand determined by the logistics demand determination module; the VR customer interaction module uses the real-time logistics process data provided by the VR real-time monitoring module to allow customers to experience and monitor the entire logistics process; the VR customer interaction module uses the realistic logistics environment provided by the VR environment simulation module to allow customers to immerse themselves in the logistics process.

4. The logistics management and control system based on big data according to claim 1 is characterized in that: The adaptive environment perception module automatically adjusts the transportation route using the real-time traffic data provided by the dynamic road condition adjustment module; The autonomous driving support module uses the transportation environment parameters provided by the adaptive environmental perception module to support the scheduling and monitoring of autonomous driving freight vehicles; the intelligent cargo identification module uses the environmental data provided by the adaptive environmental perception module to realize automatic identification and classification of cargo.

5. The logistics management and control system based on big data according to claim 1 is characterized in that: The AR real-time monitoring module uses the training data provided by the VR simulation training module to view the status of transport vehicles and goods in real time; the AR navigation assistance module uses the real-time status data provided by the AR real-time monitoring module to provide navigation assistance for the driver; the VR logistics planning module uses the training environment provided by the VR simulation training module to simulate different logistics solutions.

6. The logistics management and control system based on big data according to claim 1 is characterized in that: The transparent transport chain module uses the intelligent transport contract module to automatically execute the transport agreement and record the entire process information of the goods; the blockchain traceability module uses the recorded data provided by the transparent transport chain module to achieve full traceability of high-value and sensitive goods; the decentralized data sharing module uses the traceability data provided by the blockchain traceability module to achieve secure sharing of multi-party data.

7. The logistics management and control system based on big data according to claim 1 is characterized in that: The drone express module uses the collaborative data provided by the air-ground collaborative distribution module to quickly deliver small goods; the warehouse robot module uses the automated operation data provided by the unmanned forklift module to automatically sort, transport and load in the warehouse; the air-ground collaborative distribution module uses the delivery data provided by the drone express module to achieve integrated air-ground collaborative distribution.

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