Off-road route automation: a geospatial model for vehicle trafficability and operational path planning

Off-road trafficability planning is essential for operations in remote or infrastructure scarce environments, yet it remains a complex task due to the variability of terrain conditions and the absence of established routes. This study aims to develop an automated approach for generating off-road routes by integrating terrain trafficability modeling with a shortest-path algorithm. We present a method that combines seasonal vehicle trafficability maps with Dijkstra's algorithm, implemented in the free and replicable platform Dinamica EGO. The model allows the user to define origin destination pairs and generates three route alternatives – optimal, moderate, and challenging – based on customizable terrain cost criteria. Field validation using GNSS tracked routes showed high spatial precision, with an average match of 94.17% and RMSE not exceeding 4.95 m. Compared to recent literature, the proposed approach emphasizes operational simplicity, and adaptability to different vehicles and regions. With this, the model offers a practical and scalable solution for route planning in civil defense, military, and emergency response contexts, where decisions must be made over wild terrain. By generating route alternatives informed by trafficability conditions, the approach provides decision-makers with flexible options tailored to different operational needs.