Focusing on the problem that the existing unmanned vehicle path planning technology in complex campus environment is faced with low planning efficiency, large turning angle and poor robustness under the background of smart campus, the work aims to propose an unmanned vehicle path planning method which integrates improved A algorithm and fuzzy control DWA for the complex campus environment. Firstly, the environment obstacle information was quantified which was introduced into the A algorithm heuristic function. The global path node was optimized by selecting key nodes, and the path was smoothed by Clamped-B spline curve. Secondly, the improved fuzzy control DWA was designed, and the key nodes of global path were taken as local target points of DWA, which were dynamically set. The integrated path planning method of improved A and improved fuzzy control DWA was designed to realize the path planning of unmanned vehicles in complex campus environment. Finally, the campus unmanned vehicle experiment was carried out under the static and dynamic unknown campus environment. The improved A + DWA path planning method had better real-time obstacle avoidance performance than the other two methods, and the planned path conformed to the global path. The path trajectory deviation was small, and the average deviation was only±0.109 m, which effectively reduced the turning angle of the unmanned vehicle. The planned path was safer and more efficient, which ensured the global optimum and the smoother generated trajectory. The path planning method of unmanned vehicles in complex campus environment, which integrates improved A algorithm and fuzzy control DWA, can ensure the reliability of unmanned vehicles in campus operation and meet the needs of smart campus construction.