Intelligent scheduling and emergency management for mining areas integrating improved bidirectional A* algorithm path planning

Abstract

Intelligent scheduling and emergency management are crucial for the development of modern mining. However, traditional management approaches face several problems, including low scheduling efficiency, inadequate safety hazard monitoring, and difficulties in path planning due to complex terrain. Therefore, a path planning method combining improved bidirectional A* algorithm is proposed in this paper. The flexibility and accuracy of path planning are improved through dual-end search strategy and slope factor optimisation cost function, combined with dynamic heuristic function, and the intelligent scheduling and emergency management system of the mining area is constructed by combining digital twin technology. The experimental results show that the improved bidirectional A* algorithm is superior to the traditional method in terms of path planning efficiency, accuracy and adaptability, with 23 iterations, 23.67 m path length and 820 node extensions. The success rate in high-density obstacle areas is 97.67%, and the average in steep slope areas is 93.04%. Combined with the digital twin technology, the path adjustment time is reduced to 618.47 ms, the success rate is increased to 95.12%, the response time is reduced to 45.76 s, and the transportation time is optimised to 19.32 min in the level 6 blocking scenario, showing superior dynamic adaptability. The innovation of this research lies in the combination of improved bidirectional A* algorithm and digital twin technology. This combination provides an efficient and adaptable intelligent scheduling and emergency management method in complex mining environment. It effectively improves the efficiency of mining transportation scheduling and emergency response ability and provides technical support for the development of mining automation and intelligence.