With the development of equipment intelligence， vehicle path planning in complex off-road environments has become a key technology， which is integral to the development of military forces and the intelligence of military equipment. Several factors affect vehicle performance in off-road environments， such as obstacles， road potholes， and mud. Most path optimization algorithms for traditional urban roads are designed for existing roads and do not meet the requirements of path optimization in complex off-road environments with many unknown risks. The path optimization algorithm is less， which considers the complicated soil geological conditions of the off-road environment. Thus， based on the Bekker ground mechanics theory and improved genetic algorithm， this study proposes an improved genetic algorithm， which considers the influences of soil on the vehicle. The shortest path travel time was taken as the optimization goal， and a path optimization algorithm suitable for off-road environments was implemented. In this study， the modeling and path optimization of a field environment with obstacles and various soils were conducted. The results demonstrated that the optimization algorithm established the coupling effect between the mechanical characteristics of ground and vehicle. The obstacles， soil characteristics， and vehicle characteristics in the field environment were evaluated comprehensively， and a safe， efficient， and smooth field path for vehicles was obtained in the complex off-road environment. This algorithm provides a reference for establishing the connection between topographic mechanics and the path optimization algorithm.