Intelligent scheduling system and method for vehicle and personnel optimization management

Abstract

The invention provides an intelligent scheduling system and method for vehicle and personnel optimization management, and the system comprises a task management module which is used for receiving a transportation task, generating a scheduling task according to the related information of the transportation task, and transmitting the scheduling task to a path planning module, the operation condition of the scheduling task is managed in real time; the data acquisition module is used for acquiring historical data and real-time data and then sending the historical data and the real-time data to the data processing module; the data processing module is used for receiving historical data and real-time data, performing standardization processing on the data, and transmitting the standardized data to the path planning module; the path planning module is used for receiving the scheduling task and the standardized data, generating an optimal transportation path according to the scheduling task and the standardized data, and sending the optimal transportation path as a transportation instruction to the user interaction module; and the user interaction module is used for providing a friendly operation interface, a voice interaction function and a suggestion feedback interface for a user.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent transportation management, and in particular to an intelligent scheduling system and method for optimizing the management of vehicles and personnel. Background Art

[0002] In the construction industry, efficient execution of transportation tasks is crucial to the smooth progress of projects. Traditional vehicle and personnel scheduling methods rely on manual experience and suffer from problems such as inefficiency and resource waste, especially in terms of idle mileage and driver workload. Therefore, it is particularly necessary to develop an intelligent scheduling system that can dynamically match resources such as vehicles, parking lots, drivers, and rest areas, and achieve optimal route planning. Although existing intelligent scheduling systems have made significant progress in improving transportation efficiency, reducing costs, and optimizing resource utilization, they still have some shortcomings and challenges. The following are some common problems:

[0003] 1. Data real-time and accuracy: ① Latency: Although many intelligent dispatching systems rely on real-time data (such as traffic conditions and vehicle locations), in actual operation, data transmission may be delayed, resulting in inaccurate path planning; ② Data quality: If the input data is inaccurate or incomplete (for example, weak or lost GPS signals, untimely traffic information updates), it will affect the system's decision-making.

[0004] 2. Adaptability to complex environments: ① Insufficient handling of special scenarios: Certain specific scenarios (such as extreme weather, road construction, emergencies, etc.) may not be fully considered, resulting in the system being unable to make optimal adjustments; ② Variable task requirements: When faced with changing task requirements, the system's flexibility and response speed may be insufficient, especially when the task types are diverse and time is tight.

[0005] 3. User experience and interaction design: ① Complex user interface: The user interface design of some intelligent dispatching systems is relatively complex, and the operation is not intuitive enough, which brings inconvenience to drivers and other users; ② Insufficient feedback mechanism: The system lacks an effective user feedback mechanism and cannot obtain users' actual experience and improvement suggestions in a timely manner, which affects the continuous optimization of the system.

[0006] 4. Security and Privacy Protection: ① Information security risks: As intelligent dispatch systems increasingly rely on the internet and cloud services, the security and privacy of user data have become critical issues. Risks such as cyberattacks and data leaks require more stringent protection measures. ② Unclear liability: In the event of an accident or dispute, unclear liability definitions within the intelligent dispatch system could lead to insurance disputes.

[0007] 5. Hardware and infrastructure dependence: ① Equipment compatibility: Compatibility issues between vehicles and equipment of different brands may limit the widespread application of the system; ② Insufficient infrastructure: The communication infrastructure in some areas (such as remote areas) is not perfect, which may affect the normal operation of the system.

[0008] 6. Algorithm limitations: ① Single optimization model: Existing optimization algorithms may be too dependent on a single model and fail to fully consider multiple factors (such as cost, time, and environmental protection), resulting in less than ideal optimization results; ② High computing resource consumption: Complex path planning and task allocation algorithms may require a large amount of computing resources, especially in large-scale fleet management, which places higher demands on system performance.

[0009] 7. Lack of management regulations and standards: ① Lagging management regulations: The rapid development of intelligent dispatching systems has outpaced the formulation of relevant management regulations, resulting in certain regulatory blind spots in actual applications; ② Inconsistent industry standards: Due to the lack of unified industry standards, it is difficult for products and services from different suppliers to be interconnected, increasing users' usage costs and technical barriers.

[0010] 8. Emergency response capability: ① Limited emergency response capability: When encountering emergencies (such as traffic accidents, natural disasters, etc.), the system's emergency response capability may be insufficient, and it may not be able to quickly adjust the scheduling plan to deal with emergencies; ② Insufficient redundancy design: Some systems lack sufficient redundancy design. Once a key node fails, it may affect the normal operation of the entire system. Summary of the Invention

[0011] The purpose of the present invention is to provide an intelligent scheduling system and method for optimizing the management of vehicles and personnel, aiming to solve the above-mentioned problems in the prior art.

[0012] An embodiment of the present invention provides an intelligent scheduling system for optimizing vehicle and personnel management, including:

[0013] A task management module, connected to the user interaction module and the route planning module, for receiving transport tasks from the user interaction module, generating scheduling tasks based on relevant information of the transport tasks, transmitting the scheduling tasks to the route planning module, and managing the operation status of the scheduling tasks in real time;

[0014] A data acquisition module, connected to the data processing module, is used to collect historical data and real-time data, and send the historical data and real-time data to the data processing module; wherein the historical data includes information related to the vehicle's historical transportation tasks; the real-time data includes the vehicle's current location information, real-time traffic conditions on the transportation route, and real-time weather conditions;

[0015] a data processing module, connected to the data acquisition module and the path planning module, configured to receive the historical data and the real-time data, perform standardization on the data, and transmit the standardized data to the path planning module;

[0016] a path planning module, connected to the data processing module, the task management module, and the user interaction module, configured to receive the scheduling task and the standardized data, generate an optimal transportation path based on the scheduling task and the standardized data, and send the optimal transportation path as a transportation instruction to the user interaction module;

[0017] The user interaction module is connected to the task management module and the route planning module, and is used to provide users with a friendly operation interface, voice interaction function and suggestion feedback interface; wherein, the users include corporate personnel, transport team managers and drivers.

[0018] An embodiment of the present invention provides an intelligent scheduling method for optimizing vehicle and personnel management, comprising:

[0019] The task management module receives the transport task from the user interaction module, generates a scheduling task based on the relevant information of the transport task, transmits the scheduling task to the path planning module, and manages the operation status of the scheduling task in real time;

[0020] The data acquisition module collects historical data and real-time data, and sends the historical data and real-time data to the data processing module; wherein the historical data includes information related to the vehicle's historical transportation tasks; the real-time data includes the vehicle's current location information, real-time traffic conditions on the transportation route, and real-time weather conditions;

[0021] The data processing module receives the historical data and the real-time data, performs standardization on the data, and transmits the standardized data to the path planning module;

[0022] receiving the scheduling task and the standardized data through a path planning module, generating an optimal transportation path according to the scheduling task and the standardized data, and sending the optimal transportation path as a transportation instruction to a user interaction module;

[0023] The user interaction module provides users with a friendly operation interface, voice interaction function and suggestion feedback interface; wherein, the users include corporate personnel, transport team managers and drivers.

[0024] An embodiment of the present invention also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the steps of the above-mentioned intelligent scheduling method for optimizing the management of vehicles and personnel are implemented.

[0025] An embodiment of the present invention also provides a computer-readable storage medium, on which an implementation program for information transmission is stored. When the program is executed by a processor, the steps of the above-mentioned intelligent scheduling method for optimal management of vehicles and personnel are implemented.

[0026] The use of the embodiments of the present invention can include the following beneficial effects: The embodiments of the present invention aim to provide an intelligent scheduling system for optimizing the management of vehicles and personnel. Through real-time geographic information system (GIS) and other data, it dynamically matches resources such as vehicles, parking lots, drivers, and rest areas to optimize transportation routes, reduce empty mileage, improve transportation efficiency, and enhance the driver's work experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 Schematic diagram of an intelligent dispatching system for optimizing vehicle and personnel management according to an embodiment of the present invention;

[0029] Figure 2 This is a flow chart of an intelligent scheduling method for optimizing vehicle and personnel management according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this document.

[0031] System Example

[0032] According to an embodiment of the present invention, an intelligent scheduling system for optimizing vehicle and personnel management is provided. Figure 1 FIG is a schematic diagram of an intelligent dispatching system for optimizing vehicle and personnel management according to an embodiment of the present invention. Figure 1 As shown, the intelligent scheduling system for optimizing vehicle and personnel management according to an embodiment of the present invention specifically includes:

[0033] The task management module 10 is connected to the user interaction module and the path planning module, and is used to receive transportation tasks from the user interaction module, generate scheduling tasks based on the relevant information of the transportation tasks, transmit the scheduling tasks to the path planning module, and manage the operation status of the scheduling tasks in real time. Specifically, it is used to:

[0034] Generating a final dispatch task using a multi-objective optimization algorithm based on the relevant information of the transport task; wherein the relevant information of the transport task includes transport time, transport cost and environmental factors;

[0035] The data acquisition module 12 is connected to the data processing module and is used to collect historical data and real-time data, and send the historical data and real-time data to the data processing module; wherein the historical data includes information related to the vehicle's historical transportation tasks; the real-time data includes the vehicle's current location information, real-time traffic conditions on the transportation route, and real-time weather conditions;

[0036] The data processing module 14 is connected to the data acquisition module and the path planning module, and is used to receive the historical data and real-time data, perform standardization on the data, and transmit the standardized data to the path planning module;

[0037] a route planning module 16 connected to the data processing module, the task management module, and the user interaction module, configured to receive the scheduling task and the standardized data, generate an optimal transportation route based on the scheduling task and the standardized data, and send the optimal transportation route as a transportation instruction to the user interaction module;

[0038] A user interaction module 18 is connected to the task management module and the route planning module to provide users with a user-friendly operation interface, voice interaction function, and suggestion feedback interface; wherein the users include enterprise personnel, transport team managers, and drivers;

[0039] The system further comprises:

[0040] A driver management module, connected to the task management module and the user interaction module, for managing and scheduling drivers according to the scheduling tasks;

[0041] A parking lot management module, connected to the task management module and the user interaction module, for performing parking lot management corresponding to the driver according to the operation status of the scheduling task;

[0042] A rest area management module, connected to the task management module and the user interaction module, for managing the corresponding rest areas for drivers according to the operation status of the dispatched tasks;

[0043] A log recording module, connected to the data acquisition module, for recording key operation logs related to the transportation task using blockchain technology;

[0044] A security management module, connected to the log recording module, configured to encrypt and store the key operation logs using a multiple backup mechanism;

[0045] A hardware adaptation module, connected to the user interaction module, for providing the user with several types of connection ports;

[0046] A data analysis module, connected to the data acquisition module, the route planning module and the user interaction module, for performing real-time analysis based on the historical data, real-time data and user feedback, and dynamically optimizing and adjusting the optimal transportation route using the analysis results as adjustment instructions;

[0047] The emergency response module is connected to the task management module and is used to perform emergency management on emergencies during the scheduling task process.

[0048] The above technical solution of the embodiment of the present invention is described in detail below in conjunction with the specific situation of the intelligent scheduling system for optimal management of vehicles and personnel in the embodiment of the present invention.

[0049] The intelligent dispatching system for optimizing vehicle and personnel management proposed in the embodiment of the present invention specifically includes:

[0050] The task management module is used to receive and assign transportation tasks. This module also embeds a multi-objective optimization algorithm submodule, which comprehensively considers various factors such as time, cost, and environmental protection to generate the best scheduling plan.

[0051] Data acquisition module, used to obtain real-time data such as historical data, vehicle location, and traffic conditions;

[0052] Data processing module, used to clean and analyze data to ensure data accuracy and completeness;

[0053] Data analysis module, used to analyze historical data, real-time data and user feedback suggestions of transportation tasks to optimize future route planning and task allocation;

[0054] The route planning module is used to plan the best transport route for the vehicle based on the transport task, real-time traffic conditions and geographic information, and dynamically adjust the optimal driving route;

[0055] Parking management module to find available parking lots for drivers near loading points, unloading points and parking lots;

[0056] Driver management module, used to manage and dispatch drivers' tasks;

[0057] Rest area management module, which is used to arrange rest areas for drivers near loading and unloading points and parking lots;

[0058] The user interaction module is used to provide a simple and easy-to-use operation interface and voice interaction functions, and establish an effective user feedback mechanism; users include transport drivers, transport team managers, and corporate personnel with transport needs;

[0059] The security management module is used to ensure user information security and prevent data leakage; it uses strict data encryption technology and security protocols to strengthen security and privacy protection;

[0060] Hardware adaptation module to ensure compatibility between vehicles and devices of different brands;

[0061] The emergency response module is used to handle emergencies and ensure the normal operation of the system.

[0062] The system also includes a real-time monitoring module for monitoring the location and status of the vehicle to ensure that the task is completed on time;

[0063] It also includes a logging module based on blockchain technology to record key operation logs and prevent data tampering.

[0064] The specific implementation steps of the scheduling system proposed in the embodiment of the present invention are as follows:

[0065] 1. Task allocation and initial scheduling

[0066] Mission reception: The vehicle receives the transport mission instruction.

[0067] Route planning: The system plans the best route for the vehicle from the starting point to the loading point based on real-time traffic conditions and geographic information.

[0068] 2. Loading and waiting

[0069] Arrival at loading point: The vehicle arrives at the designated loading point and is ready to start loading operations.

[0070] Finding Available Parking and Rest Areas: When other vehicles are operating at the loading point, the system needs to find available parking lots near the loading point in real time for the driver to avoid vehicles occupying the loading and unloading area for a long time, which would affect the operation of other vehicles. It also calculates the length of time the driver needs to wait and recommends a reasonable itinerary for the driver to arrange for the waiting time. If the waiting time is long, the driver will be arranged for a rest area and the driver's itinerary will be planned in the rest area. If the waiting time is short, the driver will be advised to wait for a while. When the vehicle is ready for loading, the system needs to calculate the loading time and arrange the rest area and the driver's itinerary in the rest area based on the length of the loading operation.

[0071] For example: when driver A arrives at the loading point, driver B's vehicle is in the process of loading. In this case, driver A needs to park his vehicle in a nearby available parking lot first, and the waiting time for driver A is calculated, that is, the waiting time for driver A = the remaining loading time of driver B's vehicle. If the waiting time is less than or equal to 20 minutes, driver A is advised to wait in the parking lot. If the waiting time is greater than 20 minutes, a rest area is arranged nearby for driver A. Then, driver A's itinerary in the rest area is reasonably planned based on the waiting time: if the waiting time is 30 minutes (only enough time for a short stop), the driver is advised to return to the parking lot after having a meal and prepare for loading. If the waiting time is sufficient, other additional matters such as eating, going to the toilet, and sleeping can be arranged for driver A, and he can return to the parking lot to prepare for loading when the remaining loading time of driver B is less than or equal to 10 minutes. When driver A's vehicle is ready for loading, the time it takes for driver A's vehicle to complete the loading operation needs to be calculated. Because during this period, driver A still needs to wait for the loader to complete the loading. Therefore, the system still needs to make reasonable arrangements for driver A based on the time it takes for driver A's vehicle to complete the loading operation. If the waiting time is less than or equal to 20 minutes, driver A is advised to complete high-priority tasks first, such as going to the toilet and eating fast food. If the waiting time is relatively sufficient, driver A's itinerary will be arranged according to the priority of the tasks, such as going to the toilet first, then having a full meal (there is no need to suggest driver A to eat fast food if there is sufficient time), and finally going to sleep.

[0072] Preferably, the embodiment of the present invention does not set any limit on the threshold of the above-mentioned waiting time. The system will use a deep learning algorithm to make predictions based on the driver's historical behavior time. Because everyone's behavioral habits are different, for example, driver A only needs ten minutes to eat and five minutes to go to the toilet. When the waiting time is 20 minutes, driver A can be arranged to eat and go to the toilet, but driver B needs fifteen minutes to eat and fifteen minutes to go to the toilet. When the waiting time is 20 minutes, driver B can only be arranged to do the higher priority items first. The system will default to the priority division as: going to the toilet > eating > sleeping, etc., but the priority division can be customized by the user. For example, driver A is not hungry for the time being, but he is in a hurry to go to the toilet, then he can reorder his priority items through the mobile rest area management module and adjust them to going to the toilet > sleeping > eating, etc.

[0073] 3. Transportation and unloading

[0074] Go to the unloading point: After loading is completed, the vehicle goes to the unloading point according to the optimal route planned by the system.

[0075] Unloading and Waiting: Upon arrival at the unloading point, the vehicle completes unloading, completing the first phase of the mission. During unloading, the driver is assigned available parking lots and rest areas, using the same arrangement principles as described above for loading.

[0076] 4. Return to the parking lot and reload

[0077] Empty vehicle return to the parking lot: After unloading, the system plans the best route for the vehicle to return to the parking lot. Taking into account the cost of traveling empty, the system checks whether there are other tasks to be transported (such as other materials) that can be performed along the way.

[0078] Mid-journey task arrangement: If there are available materials that need to be transported on the way back to the parking lot, the system will dynamically adjust the plan, allowing the driver to load these materials and then return to the corresponding unloading point to unload, and finally drive back to the parking lot.

[0079] 5. Driver Rest and Rescheduling

[0080] Driver rest area: There is a rest area near the parking lot where drivers can take necessary rest to ensure safe driving.

[0081] Secondary task preparation: After the driver completes a task and has had a good rest, the system will reconfirm the task arrangement to ensure that all transportation tasks are seamlessly connected.

[0082] The embodiment of the present invention takes a specific asphalt transportation task as an example:

[0083] Starting point: Parking Lot A

[0084] Loading point: Asphalt Plant B

[0085] Unloading point: Construction location C

[0086] Return path: The system finds a temporary parking lot D and a rest area E near point B.

[0087] A vehicle departs from point A and first arrives at point B to load. After loading, it follows the optimal route to point C for unloading. After unloading, the system recommends that the vehicle stop at point D and the driver rest at point E. After the driver rests, the system instructs the vehicle to proceed to point B to load the milled material, then return to point C to unload. Finally, the vehicle prepares to return to point A and checks for other pending transport tasks along the way. In this way, the present invention not only improves transportation efficiency but also significantly reduces idle miles, achieving optimal resource allocation.

[0088] In addition to the basic configurations described above, the intelligent scheduling system proposed in this embodiment of the present invention also introduces advanced technologies to address existing system issues such as data quality, poor adaptability to complex environments, poor user experience, insufficient security and privacy protection, hardware dependence, and algorithmic limitations. Specifically, improvements include the following:

[0089] 1. Improve data quality and real-time performance: Ensure data real-time and accuracy by introducing more advanced sensor technologies and Internet of Things (IoT) devices. For example, high-precision GPS modules and Bluetooth Low Energy (BLE) technology are used to precisely locate vehicle locations. Traffic information collection terminals are integrated to obtain real-time dynamic information such as road conditions and weather changes. Furthermore, edge computing platforms are being built to shorten data transmission paths and reduce latency.

[0090] 2. Enhanced adaptability and flexibility: Introducing more intelligent algorithms and models enables the system to quickly adapt to various complex environments and changing mission requirements. For example, deep learning algorithms are introduced to automatically identify and handle special scenarios such as extreme weather and road construction; adaptive path planning algorithms are designed to dynamically adjust the optimal driving route based on real-time road conditions; and multi-objective optimization is supported, comprehensively considering factors such as time, cost, and environmental protection to generate the optimal scheduling plan.

[0091] 3. Optimize the user experience by simplifying the user interface design, providing more intuitive operation methods, and establishing an effective user feedback mechanism. For example: develop a simple and easy-to-use mobile application to allow drivers to easily view task schedules and operation guides; implement voice interaction functions, allowing drivers to complete common operations through voice commands; and establish a user evaluation system to collect user feedback and continuously improve system performance.

[0092] 4. Strengthen security and privacy protection: Adopt stricter data encryption technology and security protocols, clearly define responsibilities, and ensure user information security. For example, use blockchain technology to log key operations and prevent data tampering; strengthen network firewall configuration to resist external attacks; and formulate detailed responsibility division rules so that the system can quickly identify the person responsible in the event of an incident or dispute.

[0093] 5. Improve hardware and infrastructure: Support the promotion of equipment standardization and infrastructure construction to ensure the wide applicability and stability of the system. For example, equip unified communication protocols and interface standards to improve compatibility between different brands of vehicles and equipment.

[0094] 6. Use multi-objective optimization algorithms to comprehensively consider multiple factors such as cost, time, and environmental protection to achieve more comprehensive optimization. For example, combine genetic algorithms and particle swarm optimization algorithms to find the global optimal solution; and consider environmental factors such as carbon emissions to generate low-carbon and energy-saving scheduling plans.

[0095] 7. Establish and improve management regulations and industry standards system to promote the healthy development of intelligent dispatching system.

[0096] 8. Improve emergency response capabilities, strengthen emergency management and redundancy design, and ensure that the system can quickly adjust and resume normal operations in the event of an emergency. For example: establish an emergency command center to monitor system operation status in real time and handle emergencies promptly; introduce multiple backup mechanisms to ensure that key node failures do not affect the overall operation of the system.

[0097] To implement the above-mentioned improvement measures, the embodiment of the present invention provides the following specific structure:

[0098] 1. Hardware configuration: Select high-performance processors, large-capacity memory and high-speed network interfaces to build a stable hardware infrastructure.

[0099] 2. Software architecture: Based on microservice architecture design, it adopts containerized deployment to improve the scalability and maintainability of the system.

[0100] 3. Algorithm logic: Integrate multiple advanced algorithms, such as deep learning and genetic algorithms, to form an intelligent decision-making engine.

[0101] The embodiments of this invention have been verified through large-scale simulation tests and real-world application scenarios, demonstrating that the improved system can perform well across multiple dimensions and meet the expected goals. By comprehensively optimizing the intelligent dispatching system, the embodiments of this invention address numerous issues existing in the prior art, significantly improving system performance and service quality (increasing transportation efficiency, reducing operating costs, and optimizing resource utilization), and have broad application prospects.

[0102] Method Example

[0103] According to an embodiment of the present invention, an intelligent scheduling method for optimizing vehicle and personnel management is provided. Figure 2 This is a flow chart of an intelligent scheduling method for optimizing vehicle and personnel management according to an embodiment of the present invention. Figure 2 As shown, the intelligent scheduling method for optimizing vehicle and personnel management according to an embodiment of the present invention specifically includes:

[0104] Step S201: receiving a transport task from a user interaction module through a task management module, generating a scheduling task based on relevant information of the transport task, transmitting the scheduling task to a path planning module, and managing the operation status of the scheduling task in real time;

[0105] Step S202: The data collection module collects historical data and real-time data, and sends the historical data and real-time data to the data processing module; wherein the historical data includes information related to the vehicle's historical transportation tasks; the real-time data includes the vehicle's current location information, real-time traffic conditions on the transportation route, and real-time weather conditions;

[0106] Step S203: receiving the historical data and real-time data through the data processing module, performing standardization on the data, and transmitting the standardized data to the path planning module;

[0107] Step S204: receiving the scheduling task and the standardized data through a path planning module, generating an optimal transportation path according to the scheduling task and the standardized data, and sending the optimal transportation path as a transportation instruction to a user interaction module;

[0108] Step S205: providing a user-friendly operation interface, voice interaction function, and suggestion feedback interface to users through a user interaction module; wherein the users include enterprise personnel, transport team managers, and drivers;

[0109] The method further comprises:

[0110] Managing and dispatching drivers according to the dispatch tasks through the driver management module;

[0111] Carry out corresponding parking lot management for drivers according to the operation status of the scheduling task through the parking lot management module;

[0112] The rest area management module manages the drivers' rest areas accordingly according to the operation status of the dispatching tasks;

[0113] Using blockchain technology to record key operation logs related to the transportation task through the logging module;

[0114] The key operation log is encrypted and stored using a multiple backup mechanism through a security management module;

[0115] Several types of connection ports are provided to users through hardware adapter modules.

[0116] The embodiment of the present invention is a method embodiment corresponding to the above-mentioned system embodiment. The specific operation of each step can be understood by referring to the description of the system embodiment, and will not be repeated here.

[0117] In summary, the embodiments of the present invention, through the application of an intelligent dispatching system, solve the problems of low efficiency and waste of resources in traditional transportation dispatching, significantly improve transportation efficiency, reduce operating costs, enhance the driver's work experience, and enhance dispatching flexibility. Therefore, the intelligent dispatching system proposed in the embodiments of the present invention will be more intelligent, efficient, and reliable, and can better serve various transportation and logistics needs. The embodiments of the present invention specifically include the following beneficial effects:

[0118] 1. Improve transportation efficiency: Through dynamic route planning and task optimization, idle time and mileage are reduced, and transportation efficiency is improved.

[0119] 2. Reduce operating costs: Reducing idle mileage means lower fuel consumption and maintenance costs, thereby reducing overall operating costs.

[0120] 3. Improve driver experience: Reasonable arrangement of rest areas and parking spaces ensures that drivers have enough rest time, improving work comfort and safety.

[0121] 4. Enhanced scheduling flexibility: The system can flexibly adjust task arrangements based on real-time conditions to ensure maximum resource utilization.

[0122] Device Example 1

[0123] An embodiment of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps described in the method embodiment when executed by the processor.

[0124] Device Example 2

[0125] An embodiment of the present invention provides a computer-readable storage medium, on which a program for implementing information transmission is stored. When the program is executed by a processor, the steps described in the method embodiment are implemented.

[0126] The computer-readable storage medium in this embodiment includes, but is not limited to, ROM, RAM, magnetic disk, or optical disk.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent dispatching system for optimizing vehicle and personnel management, characterized by include: A task management module, connected to the user interaction module and the route planning module, for receiving transport tasks from the user interaction module, generating scheduling tasks based on relevant information of the transport tasks, transmitting the scheduling tasks to the route planning module, and managing the operation status of the scheduling tasks in real time; A data acquisition module, connected to the data processing module, is used to collect historical data and real-time data, and send the historical data and real-time data to the data processing module; wherein the historical data includes information related to the vehicle's historical transportation tasks; the real-time data includes the vehicle's current location information, real-time traffic conditions on the transportation route, and real-time weather conditions; a data processing module, connected to the data acquisition module and the path planning module, configured to receive the historical data and the real-time data, perform standardization on the data, and transmit the standardized data to the path planning module; a route planning module, connected to the data processing module, the task management module, and the user interaction module, configured to receive the scheduling task and the standardized data, generate an optimal transportation route based on the scheduling task and the standardized data, and send the optimal transportation route as a transportation instruction to the user interaction module; The user interaction module is connected to the task management module and the route planning module, and is used to provide users with a friendly operation interface, voice interaction function and suggestion feedback interface; wherein, the users include enterprise personnel, transport team managers and drivers.

2. The system according to claim 1, wherein: The system further comprises: A driver management module, connected to the task management module and the user interaction module, for managing and scheduling drivers according to the scheduling tasks; A parking lot management module, connected to the task management module and the user interaction module, for performing parking lot management corresponding to the driver according to the operation status of the scheduling task; The rest area management module is connected to the task management module and the user interaction module, and is used to manage the corresponding rest areas for drivers according to the operation status of the scheduling task.

3. The system according to claim 1, wherein: The system further comprises: A log recording module, connected to the data acquisition module, for recording key operation logs related to the transportation task using blockchain technology; A security management module, connected to the log recording module, configured to encrypt and store the key operation logs using a multiple backup mechanism; The hardware adaptation module is connected to the user interaction module and is used to provide the user with several types of connection ports.

4. The system according to claim 1, wherein: The system further comprises: A data analysis module, connected to the data acquisition module, the route planning module and the user interaction module, for performing real-time analysis based on the historical data, real-time data and user feedback, and dynamically optimizing and adjusting the optimal transportation route using the analysis results as adjustment instructions; The emergency response module is connected to the task management module and is used to perform emergency management on emergencies during the scheduling task process.

5. The system according to claim 1, wherein: The task management module is specifically used for: The final scheduling task is generated through a multi-objective optimization algorithm based on the relevant information of the transportation task; wherein the relevant information of the transportation task includes transportation time, transportation cost and environmental factors.

6. An intelligent scheduling method for optimizing vehicle and personnel management, characterized in that include: The task management module receives the transport task from the user interaction module, generates a scheduling task based on the relevant information of the transport task, transmits the scheduling task to the path planning module, and manages the operation status of the scheduling task in real time; The data acquisition module collects historical data and real-time data, and sends the historical data and real-time data to the data processing module; wherein the historical data includes information related to the vehicle's historical transportation tasks; the real-time data includes the vehicle's current location information, real-time traffic conditions on the transportation route, and real-time weather conditions; The data processing module receives the historical data and the real-time data, performs standardization on the data, and transmits the standardized data to the path planning module; receiving the scheduling task and the standardized data through a path planning module, generating an optimal transportation path according to the scheduling task and the standardized data, and sending the optimal transportation path as a transportation instruction to a user interaction module; The user interaction module provides users with a friendly operation interface, voice interaction function and suggestion feedback interface; wherein, the users include corporate personnel, transport team managers and drivers.

7. The method according to claim 6, characterized in that The method further comprises: Managing and dispatching drivers according to the dispatch tasks through the driver management module; Carry out corresponding parking lot management for drivers according to the operation status of the scheduling task through the parking lot management module; The rest area management module manages the drivers' rest areas accordingly according to the operation status of the dispatching tasks.

8. The method according to claim 6, characterized in that The method further comprises: Using blockchain technology to record key operation logs related to the transportation task through the logging module; The key operation log is encrypted and stored using a multiple backup mechanism through a security management module; Several types of connection ports are provided to users through hardware adapter modules.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the intelligent scheduling method for optimizing management of vehicles and personnel as described in any one of claims 6 to 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores an implementation program for information transmission, and when the program is executed by the processor, the steps of the intelligent scheduling method for optimal management of vehicles and personnel as described in any one of claims 6 to 8 are implemented.

Images