At present, the research on unmanned mine truck system on-board decision system in mine scenarios at home and abroad is still in the initial stage, and its research focus is mainly on global planning and scheduling to improve overall safety and efficiency of the system, while ignoring the research on the mine truck independent decision method based on the global planning and scheduling. In order to further improve the safety and efficiency of the system, this paper focuses on the two core functions of behavior decision-making and motion planning under the mining truck independent decision-making method of the vehicle decision-making system. Behavior decision includes driving mode and task mode decision, collision warning and protection decision, fault classification and safety oriented decision, based on the double layer limited state machine method to realize mine truck autonomous decision protection judgment, to ensure that the vehicle in the "loading, transportation, unloading" whole process scenario of mine to improve the safety of vehicle operation. Motion planning includes speed planning and path planning. This paper adopts the quadratic programming algorithm based on the shortest time and the optimal energy consumption to solve the speed planning, and adopts the hybrid A-star and curve fitting algorithm based on special scenarios to solve the local path planning, so that the operation efficiency can be improved by 10%~20% in the loading and unloading parking scenario. The system has been production and operation in a mining area in northern China for half a year. The real vehicle production and operation results show that the system can effectively improve the vehicle operation efficiency and safety ability to avoid obstacles.