Development of an optimal route planning algorithm using hot zones

The authors in the article address the problem of planning optimal routes in a dynamic environment using OpenStreetMap (OSM) geographic data for the territory of Ukraine. Amid conflict situations and active hostilities, there is a need to adapt classical route-finding algorithms to account for specific terrain constraints. The main aim of the research is to develop an adaptive A* algorithm that considers high-risk areas ("hot zones") which can significantly impact the efficiency and safety of the calculated route. To achieve this goal, the authors conducted an analysis of existing shortest path search algorithms using the classic A* algorithm and its heuristic function, which considers the distance between route points. The study explores a modified version of the A* algorithm that includes an additional cost factor for "hot zones." The proposed approach introduces an adaptive multiplier that restricts route planning through dangerous areas. To validate the proposed method, OSM data containing only basic road information, without military restrictions, was used. This limitation highlights the importance of additional analysis of factors such as safety and risk in route planning. The results demonstrate the effectiveness of the developed adaptive A* algorithm in constructing routes in a dynamic environment, particularly with the ability to avoid dangerous ("hot") zones. The study's conclusions confirm that adding a cost factor in "hot zones" improves route accuracy and enhances travel safety. The developed algorithm can be applied to automated route planning in scenarios where it is crucial to consider variable risk factors and specific terrain conditions.