We propose a path planning method for autonomous vehicle in cluttered environment with narrow passages. Different from traditional methods, we use a learning approach based on RBF kernel SVM to maximize the safety margin for driving. We use the Lagrange multipliers of SVM dual model to find most critical points in map and generate optimized hyperplane for path. The method is implemented on autonomous vehicle for outdoor parking and compared to well-known method in autonomous vehicle literatures. The experiments prove that the method is able to generate smooth and safe path in shorter time compared to other methods.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.