Abstract: The existing planning algorithms can not properly solve the motion planning problem of intelligent vehicle in complex environments with many irregular and random obstacles. To solve the problem, a simple and practical RRT-based algorithm, continuous-curvature RRT algorithm, is proposed. This algorithm combines the environmental constraints and the constraints of intelligent vehicle with RRTs. Firstly, a goal-biased sampling strategy and a reasonable metric function are introduced to greatly increase the planning speed and quality. And then, a post-processing method based on the maximum curvature constraint is presented to generate a smooth, continuous-curvature and executable trajectory. Simulation experiments and real intelligent vehicle test verify the correctness, validity and practicability of this algorithm.