Abstract: After many years' development, the driverless technology has gradually matured and has begun to be widely used in vehicles. At the same time, it will also become an important way to realize an efficient, safe and intelligent transportation for trackless rubber tyred vehicles underground. However, being different from the mature driverless technology of surface vehicles, there are still many problems to be solved when driverless technology is applied underground. Aiming at the problems of low efficiency and frequent accidents of underground manually driven trackless rubber tyred vehicles, taking unmanned trackless rubber tyred vehicles as the research object, the underground path planning method is studied through simulation and test. Firstly, by analyzing and comparing the advantages and disadvantages of common path planning algorithms, the optimal A* algorithm and artificial potential field algorithm are selected as the basic algorithms for the global and local path planning of unmanned trackless rubber tyred vehicles. Secondly, aiming at the problems of many search nodes and uneven path of the traditional A* algorithm for global path planning, the methods of exponential function weighting and cubic spline interpolation are used to improve it respectively. The improved algorithm is simulated in the underground roadway. The results show that the number of search nodes of the improved algorithm is reduced by 50%. In the same scenario, the time required to plan the path is only 20% of that of the traditional A* algorithm, the efficiency of path planning has been greatly improved, and the generated path is smoother and has better continuity. At the same time, aiming at the problems of unreachable target and local optimal solution in the artificial potential field algorithm, the repulsion potential field correction factor and escape force are introduced respectively, and the relative velocity potential field is established to improve it. The simulation results show that the improved artificial potential field algorithm can plan a more reasonable driving path in various scenarios, and the safety is guaranteed. Finally, using the micro unmanned vehicle test platform, the simulated underground roadway environment is built according to the scale of 8∶1, and the obstacle free and obstacle path tracking tests of the path planning algorithm before and after the improvement of the unmanned trackless rubber tyred vehicle are carried out respectively. The results show that the path planned based on the improved A*-artificial potential field joint algorithm is more reasonable, the maximum tracking error of obstacle free planning path in the 8∶1 scale building simulation underground roadway environment is only 0.031 2 m. When meeting and avoiding obstacles in the roadway, it can plan a reasonable driving path, and the maximum deviation is only 0.035 3 m, which can meet the underground driverless requirements of trackless rubber tyred vehicles.