Auxiliary transportation scheduling management system for coal mine

Abstract

The invention belongs to the technical field of dispatching management systems, and particularly relates to a coal mine auxiliary transportation dispatching management system. Comprising an intelligent collaborative scheduling platform, a multi-modal conflict resolution routing engine, a self-adaptive active anti-collision module, an edge decision node, an elastic layered network architecture, a carrier intelligent terminal cluster, a roadway traffic control device cluster, a dynamic task redistribution module and a digital twinborn simulation module. The coal mine auxiliary transportation scheduling management system greatly improves the efficiency and safety of coal mine auxiliary transportation. The intelligent collaborative scheduling platform can generate an optimal cross-transport scheduling scheme according to a carrier capability model and a task chain decomposition technology, so that efficient collaborative operation of various carriers is realized, and idle waiting time and invalid operation of vehicles are reduced. The multi-modal conflict resolution routing engine accurately plans a conflict-free path through spatio-temporal trajectory prediction and conflict detection, and traffic jam and collision accidents in a roadway are effectively avoided.

Description

Technical Field

[0001] This invention belongs to the technical field of scheduling and management systems, and specifically relates to a coal mine auxiliary transportation scheduling and management system. Background Technology

[0002] In coal mining operations, auxiliary transportation plays a crucial role, involving the efficient and orderly transport and allocation of personnel, materials, and coal through complex underground tunnel networks. However, the field of auxiliary transportation in coal mines currently faces many pressing technical bottlenecks and challenges. Traditional transportation scheduling methods often rely on manual experience for task allocation and route planning. This approach is not only inefficient but also inadequate in dealing with the changing underground environment and unforeseen circumstances, making it difficult to make timely and accurate decisions. This can easily lead to transportation delays, traffic congestion, and even safety accidents.

[0003] From a transportation perspective, various vehicles such as trackless rubber-tired vehicles, monorail cranes, and ground-rail vehicles each have their advantages and applicable scenarios in coal mine transportation, but they lack an effective coordination and linkage mechanism. Each vehicle operates independently, without a unified scheduling system, which undoubtedly further reduces overall transportation efficiency and increases management difficulty. Moreover, at key locations such as roadway intersections and bottleneck areas, the rudimentary and low-intelligence traffic control facilities cannot dynamically adjust based on real-time traffic flow and vehicle priority, making these areas frequent bottlenecks in transportation. Existing collision avoidance methods are mostly single-function and struggle to reliably and accurately identify risks and respond effectively in harsh environments, resulting in a persistently high accident risk. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a coal mine auxiliary transportation scheduling and management system. This system aims to overcome the problems of low scheduling efficiency, poor vehicle coordination, weak control of key areas, and insufficient collision avoidance performance in existing coal mine auxiliary transportation systems.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A coal mine auxiliary transportation dispatching and management system, comprising: The intelligent collaborative scheduling platform connects trackless rubber-tired vehicles, monorail cranes, and ground rail vehicles, and generates cross-transportation scheduling solutions based on vehicle capacity models and task chain decomposition. A multimodal conflict resolution routing engine, connected to the intelligent collaborative scheduling platform, plans conflict-free paths through spatiotemporal trajectory prediction and conflict detection; The adaptive active collision avoidance module includes an environmental perception unit, a dynamic risk assessment unit, and a response execution unit. The dynamic risk assessment unit is configured with an adaptive early warning mechanism. Edge decision nodes are deployed in key areas of the alleyway and generate collision avoidance commands based on local sensor data. A flexible, layered network architecture that supports the environment perception layer, data transmission layer, decision application layer, and control execution layer. Vehicle intelligent terminal cluster, integrating positioning module, communication unit and sensor fusion interface; lane traffic control device cluster, deployed at intersections and bottleneck areas, including traffic lights and access control gates; The dynamic task reallocation module responds to vehicle failures or path congestion by reallocating the load; the digital twin simulation module simulates the scheduling scheme and outputs a collision avoidance strategy evaluation report.

[0006] The sensor fusion interface supports data access from millimeter-wave radar, UWB and infrared thermal imagers, and processes the data through a multi-sensor confidence optimization mechanism. The optimization mechanism is implemented by: establishing a mapping table between dust concentration, humidity and sensor accuracy; dynamically weighting and fusing multi-sensor data based on environmental data; and selecting the data source with confidence exceeding the threshold when data conflicts occur.

[0007] The operating duration of the traffic lights is dynamically optimized based on the vehicle traffic flow model; the access control gate is opened and closed according to the priority passage strategy of the intelligent collaborative scheduling platform.

[0008] The vehicle behavior prediction unit builds a motion model based on historical data, predicts sudden lane changes or emergency stops, and outputs the results to the dynamic risk assessment unit to trigger preventive protection strategies.

[0009] The dynamic task redistribution module uses a load balancing algorithm to generate a redistribution scheme based on the vehicle's real-time location, remaining capacity, and task urgency, and synchronously updates the path conflict detection parameters of the routing engine; the traffic lights and permission response barriers are linked and controlled according to the updated path.

[0010] When local data conflicts with global information, the edge decision node prioritizes executing collision avoidance decisions based on local data.

[0011] The communication unit supports heterogeneous communication with the intelligent collaborative scheduling platform, the multimodal conflict resolution routing engine, the adaptive active collision avoidance module, and the roadway traffic control device cluster.

[0012] The digital twin simulation module optimizes the warning threshold, response strategy, and path planning algorithm based on real-time data from the adaptive active collision avoidance module and conflict records from the multimodal conflict resolution routing engine.

[0013] The response execution unit includes a three-level response mechanism: audible and visual warning, speed suppression, and emergency braking.

[0014] Compared with the prior art, the beneficial effects of this invention are: This coal mine auxiliary transportation scheduling and management system significantly improves the efficiency and safety of coal mine auxiliary transportation. The intelligent collaborative scheduling platform generates optimal cross-transportation scheduling schemes based on vehicle capacity models and task chain decomposition technology, enabling efficient collaborative operation of multiple vehicles and reducing vehicle idle time and ineffective operation. The multimodal conflict resolution routing engine accurately plans conflict-free paths through spatiotemporal trajectory prediction and conflict detection, effectively avoiding traffic congestion and collisions within the tunnels.

[0015] The adaptive active collision avoidance module, combining environmental perception and dynamic risk assessment, can promptly and accurately identify collision risks in complex underground environments and effectively prevent accidents through a three-level response mechanism, further enhancing the system's safety performance. Edge decision nodes rapidly generate collision avoidance commands based on local data in key areas of the tunnel, collaborating with global scheduling to ensure transportation safety in complex traffic areas. The resilient hierarchical network architecture enables efficient system integration and stable operation, ensuring smooth data interaction and rapid processing at all levels.

[0016] The close coordination between the intelligent terminal cluster of vehicles and the roadway traffic control device cluster enables real-time monitoring and precise control of vehicle operating status. Dynamic regulation of traffic lights and access control gates optimizes roadway traffic flow. The dynamic task redistribution module can quickly respond to emergencies and rationally adjust task allocation to ensure the continuity and efficiency of transportation tasks. The digital twin simulation module provides strong support for continuous system optimization. Through pre-simulation and evaluation of scheduling schemes and collision avoidance strategies, system parameters are continuously optimized, resulting in a comprehensive improvement in the efficiency, safety, and intelligence level of the entire coal mine auxiliary transportation system, effectively promoting the modernization of the coal mine auxiliary transportation industry. Attached Figure Description

[0017] Figure 1 This is a connection block diagram of the present invention. Detailed Implementation

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0019] like Figure 1 As shown, a coal mine auxiliary transportation scheduling and management system includes: The intelligent collaborative scheduling platform integrates trackless rubber-tired vehicles, monorail cranes, and ground-rail vehicles, generating cross-transportation scheduling solutions based on vehicle capability models and task chain decomposition. Specifically, the platform is deployed in a data center, connecting all trackless rubber-tired vehicles, monorail cranes, and ground-rail vehicles within the coal mine. Detailed vehicle capability models are established for each type of vehicle, covering parameters such as load capacity, speed, range, and operational stability. Simultaneously, for each transportation task, task chain decomposition technology is used to break it down into multiple sub-tasks. Based on the capability models of each vehicle, current roadway traffic conditions, and task urgency, complex algorithms generate cross-transportation scheduling solutions. For example, during peak coal transportation periods, trackless rubber-tired vehicles and monorail cranes can be rationally coordinated to ensure coal can be transported quickly and efficiently from the mining face to designated storage or processing locations.

[0020] The multimodal conflict resolution routing engine connects to the intelligent collaborative scheduling platform, planning conflict-free paths through spatiotemporal trajectory prediction and conflict detection. Specifically, the multimodal conflict resolution routing engine is connected to the intelligent collaborative scheduling platform to receive real-time dynamic data such as vehicle position and speed. Using a spatiotemporal trajectory prediction algorithm, based on the vehicle's current driving status and historical driving patterns, its spatiotemporal trajectory over a future period is predicted. Simultaneously, considering factors such as the physical layout of the roadway and traffic rules, a conflict detection algorithm analyzes the trajectories of each vehicle. Once a potential path conflict is detected, such as two vehicles about to enter the same intersection at the same time, a conflict-free path is promptly planned, adjusting the vehicle's route or speed to ensure smooth and safe traffic during coal mine transportation.

[0021] The adaptive active collision avoidance module includes an environmental perception unit, a dynamic risk assessment unit, and a response execution unit. The dynamic risk assessment unit is configured with an adaptive early warning mechanism.

[0022] Environmental perception unit: Millimeter-wave radar, UWB positioning module, infrared thermal imager and other equipment are installed on the vehicle. These devices continuously collect information about the surrounding environment during the operation of the vehicle, including the distance to vehicles in front and behind, relative speed, the position of personnel in the alley and the distribution of heat sources in the alley, so as to provide comprehensive data support for subsequent risk assessment.

[0023] The dynamic risk assessment unit receives data from the environmental perception unit in real time, builds a risk assessment model based on deep learning algorithms, and comprehensively considers factors such as the vehicle's own speed, distance to surrounding vehicles, and complexity of the alleyway to dynamically assess the collision risk level of the vehicle in the current environment. It is also equipped with an adaptive warning mechanism that automatically adjusts the warning threshold and method according to changes in the risk level. For example, when the risk level gradually rises from low to medium risk, the volume of the warning sound increases and the flashing frequency of the warning lights increases.

[0024] Response Execution Unit: Based on the assessment results of the dynamic risk assessment unit, the corresponding response mechanism is activated. When the risk is low, only an audible and visual warning is triggered to alert the driver; if the risk increases further, the speed suppression function is activated to automatically control the vehicle's throttle or brakes to reduce the vehicle speed; in the event of an emergency collision risk, emergency braking is immediately executed to minimize the occurrence of a collision.

[0025] Edge decision nodes, deployed in key areas of the tunnel, generate collision avoidance commands based on local sensor data. Specifically, edge decision nodes are deployed in key areas of the tunnel, such as intersections, curves, and ramps. Each node is equipped with local sensors to collect real-time environmental data within a small surrounding area, such as vehicle distance, speed, and information on obstacles within the tunnel. Based on this local data, and using pre-defined collision avoidance rules and algorithms, collision avoidance commands are quickly generated. For example, when two vehicles are detected to be about to collide at an intersection, the edge decision node will immediately send deceleration or stopping commands to both vehicles, ensuring transportation safety in that critical area.

[0026] The flexible layered network architecture supports the environmental perception layer, data transmission layer, decision application layer, and control execution layer. The environmental perception layer deploys various sensors, such as millimeter-wave radar, UWB positioning base stations, and infrared thermal imagers installed at regular intervals on the inner wall of the tunnel, to collect comprehensive environmental and vehicle information in the transportation scenario, including dust concentration, humidity, vehicle position, speed, and thermal imaging data.

[0027] The data transmission layer uses an industrial-grade wired network (such as mining Ethernet) in conjunction with a wireless communication module (such as a 5G private network) to efficiently and stably transmit the data from the environmental perception layer to the data center where the intelligent collaborative scheduling platform is located, while ensuring smooth communication between modules and guaranteeing the real-time performance and accuracy of data interaction.

[0028] The decision application layer runs key software systems such as the intelligent collaborative scheduling platform, the multimodal conflict resolution routing engine, and the adaptive active collision avoidance module, and analyzes and makes decisions based on the collected data; the control execution layer connects the roadway traffic control device cluster and the vehicle intelligent terminal cluster, and precisely controls various equipment according to the instructions of the decision application layer.

[0029] The vehicle-mounted intelligent terminal cluster integrates positioning modules, communication units, and sensor fusion interfaces. Specifically, each trackless rubber-tired vehicle, monorail crane, and ground rail vehicle integrates an intelligent terminal. Its positioning module employs high-precision UWB positioning technology, combined with the vehicle's inertial navigation system, to achieve precise positioning within tunnels, with centimeter-level accuracy. The communication unit supports multiple communication protocols, enabling real-time data interaction with the intelligent collaborative scheduling platform, uploading vehicle location and status information, and receiving scheduling instructions and route planning information from the platform. The sensor fusion interface supports access to millimeter-wave radar, UWB, and infrared thermal imagers. By establishing a mapping table between dust concentration, humidity, and sensor accuracy, and based on real-time environmental data, it dynamically weights and fuses multi-sensor data. When data conflicts occur, it prioritizes data sources with confidence levels exceeding a threshold, ensuring accurate and reliable data for subsequent decision-making.

[0030] A cluster of traffic control devices, deployed at intersections and bottleneck areas, includes traffic lights and access-response gates. Specifically, traffic control devices are deployed at intersections and bottleneck areas of the lanes. The traffic lights dynamically optimize their operating duration based on a vehicle flow model, monitoring vehicle traffic flow through the area in real time and adjusting green and red light durations using intelligent algorithms to ensure smooth traffic flow. Access-response gates are connected to an intelligent collaborative scheduling platform. Based on the platform's priority passage strategy, the gates automatically open when vehicles performing critical tasks or carrying important materials need to pass, ensuring their priority passage and improving transportation efficiency.

[0031] The dynamic task redistribution module responds to vehicle malfunctions or path congestion by redistributing load. Specifically, it monitors vehicle status and roadway traffic conditions in real time. When a vehicle malfunctions (e.g., a sudden mechanical failure preventing further movement) or a path is blocked (e.g., a landslide or temporary obstacle), the dynamic task redistribution module is immediately activated. Employing a load balancing algorithm, it comprehensively considers the real-time location of remaining vehicles, remaining capacity, and task urgency to quickly generate a redistribution plan. This plan reassigns affected tasks to suitable vehicles and simultaneously updates the path conflict detection parameters of the multimodal conflict resolution routing engine. Traffic lights and access control gates are also linked to the updated path to ensure smooth task execution.

[0032] The digital twin simulation module pre-simulates the scheduling scheme and outputs a collision avoidance strategy evaluation report. Specifically, based on the scheduling scheme provided by the intelligent collaborative scheduling platform and the data generated by the adaptive active collision avoidance module and the multimodal conflict resolution routing engine, a digital twin model of the coal mine auxiliary transportation system is constructed. The scheduling scheme is pre-simulated in a virtual environment, simulating various possible scenarios, including normal transportation and sudden failures. Based on the pre-simulation results, a collision avoidance strategy evaluation report is output, analyzing the effectiveness, feasibility, and potential improvement space of the collision avoidance strategy, providing a strong basis for continuous system optimization. Simultaneously, real-time data from the adaptive active collision avoidance module and conflict records from the multimodal conflict resolution routing engine are monitored to further optimize the early warning threshold, response strategy, and path planning algorithm, improving the overall system performance.

[0033] Through the implementation of the above modules, an efficient and safe coal mine auxiliary transportation scheduling and management system is built, which effectively ensures the smooth operation of coal mine transportation and reduces the accident rate.

[0034] The above description only illustrates preferred embodiments of the present invention, but the present invention is not limited to the above embodiments.

Claims

1. A coal mine auxiliary transportation scheduling and management system, characterized in that, include: The intelligent collaborative scheduling platform connects trackless rubber-tired vehicles, monorail cranes, and ground rail vehicles, and generates cross-transportation scheduling solutions based on vehicle capacity models and task chain decomposition. A multimodal conflict resolution routing engine, connected to the intelligent collaborative scheduling platform, plans conflict-free paths through spatiotemporal trajectory prediction and conflict detection; The adaptive active collision avoidance module includes an environmental perception unit, a dynamic risk assessment unit, and a response execution unit. The dynamic risk assessment unit is configured with an adaptive early warning mechanism. Edge decision nodes are deployed in key areas of the alleyway and generate collision avoidance commands based on local sensor data. A flexible, layered network architecture that supports the environment perception layer, data transmission layer, decision application layer, and control execution layer. Vehicle intelligent terminal cluster, integrating positioning module, communication unit and sensor fusion interface; lane traffic control device cluster, deployed at intersections and bottleneck areas, including traffic lights and access control gates; The dynamic task reallocation module responds to vehicle failures or path congestion by reallocating the load; the digital twin simulation module simulates the scheduling scheme and outputs a collision avoidance strategy evaluation report.

2. The coal mine auxiliary transportation dispatching and management system according to claim 1, characterized in that: The sensor fusion interface supports data access from millimeter-wave radar, UWB and infrared thermal imagers, and processes the data through a multi-sensor confidence optimization mechanism. The optimization mechanism is implemented by: establishing a mapping table between dust concentration, humidity and sensor accuracy; dynamically weighting and fusing multi-sensor data based on environmental data; and selecting the data source with confidence exceeding the threshold when data conflicts occur.

3. The coal mine auxiliary transportation dispatching and management system according to claim 1, characterized in that: The operating duration of the traffic lights is dynamically optimized based on the vehicle traffic flow model; the access control gate is opened and closed according to the priority passage strategy of the intelligent collaborative scheduling platform.

4. The coal mine auxiliary transportation dispatching and management system according to claim 1, characterized in that: The vehicle behavior prediction unit builds a motion model based on historical data, predicts sudden lane changes or emergency stops, and outputs the results to the dynamic risk assessment unit to trigger preventive protection strategies.

5. The coal mine auxiliary transportation dispatching and management system according to claim 1, characterized in that: The dynamic task redistribution module uses a load balancing algorithm to generate a redistribution scheme based on the vehicle's real-time location, remaining capacity, and task urgency, and synchronously updates the path conflict detection parameters of the routing engine; the traffic lights and permission response barriers are linked and controlled according to the updated path.

6. The coal mine auxiliary transportation dispatching and management system according to claim 1, characterized in that: When local data conflicts with global information, the edge decision node prioritizes executing collision avoidance decisions based on local data.

7. A coal mine auxiliary transportation dispatching and management system according to claim 1, characterized in that: The communication unit supports heterogeneous communication with the intelligent collaborative scheduling platform, the multimodal conflict resolution routing engine, the adaptive active collision avoidance module, and the roadway traffic control device cluster.

8. A coal mine auxiliary transportation dispatching and management system according to claim 1, characterized in that: The digital twin simulation module optimizes the warning threshold, response strategy, and path planning algorithm based on real-time data from the adaptive active collision avoidance module and conflict records from the multimodal conflict resolution routing engine.

9. A coal mine auxiliary transportation dispatching and management system according to claim 1, characterized in that: The response execution unit includes a three-level response mechanism: audible and visual warning, speed suppression, and emergency braking.

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