An intent inference based dynamic obstacle avoidance method for intelligent vehicle in structured environment

Abstract

In this paper, a novel intent inference based dynamic obstacle avoidance method is described that is effective for both normal moving obstacles and maneuvering obstacles, therefore taking advantages of information from different sensors and electronic map. Unlike many of the methods discussed in literature our approach is based on inferring the intent of moving obstacles. It avoids the prediction of accurate maneuvering trajectories which usually fails as the motion is nonlinear and difficult to be modeled. With this method, the performance of dynamic obstacle avoidance is improved which enables the intelligent vehicle to navigate autonomously among moving obstacles. A linear model is used when no maneuver intent is detected and, otherwise, the intent of changing lane is inferred by combing its dynamic features and the road structure when the obstacle is maneuvering. Then a potential collision point will be worked out and avoided to ensure the intelligent vehicle collision free. Experiments show that our method bears significant performance.