In recent years, the increasing prevalence and intensity of wildfires have posed significant challenges to emergency response teams. The utilization of unmanned aerial vehicles (UAVs), commonly known as drones, has shown promise in aiding wildfire management efforts. This work focuses on the development of an optimal wildfire escape route planning system specifically designed for drones, considering dynamic fire and smoke models. First, the location of the source of the wildfire can be well located by information fusion between UAV and satellite, and the road conditions in the vicinity of the fire can be assessed and analyzed using multi-channel remote sensing data. Second, the road network can be extracted and segmented in real time using UAV vision technology, and each road in the road network map can be given priority based on the results of road condition classification. Third, the spread model of dynamic fires calculates the new location of the fire source based on the fire intensity, wind speed and direction, and the radius increases as the wildfire spreads. Smoke is generated around the fire source to create a visual representation of a burning fire. Finally, based on the improved A* algorithm, which considers all the above factors, the UAV can quickly plan an escape route based on the starting and destination locations that avoid the location of the fire source and the area where it is spreading. By considering dynamic fire and smoke models, the proposed system enhances the safety and efficiency of drone operations in wildfire environments.

翻译：近年来，野火频发且强度加剧，对应急响应团队构成重大挑战。无人机在野火管理中的应用已展现出潜力。本文聚焦于开发专为无人机设计的考虑动态火情与烟雾模型的最优野火逃生路径规划系统。首先，通过无人机与卫星的信息融合可精准定位野火火源位置，并利用多通道遥感数据评估分析火场周边道路状况。其次，基于无人机视觉技术可实时提取并分割道路网络，依据道路分类结果为路网图中每条道路设定优先级。再次，动态火势蔓延模型根据火强度、风速及风向计算火源新位置，火势蔓延半径随野火扩散而增大，并生成火源周围烟雾的视觉表征。最终，基于融合上述因素的改进A*算法，无人机可根据起止位置快速规划避开火源及蔓延区域的逃生路径。通过引入动态火情与烟雾模型，所提系统提升了无人机在野火环境中的安全性与作业效率。