Abstract
AbstractWe present the motion planning framework for an autonomous vehicle navigating through urban environments. Such environments present a number of motion planning challenges, including ultrareliability, high‐speed operation, complex intervehicle interaction, parking in large unstructured lots, and constrained maneuvers. Our approach combines a model‐predictive trajectory generation algorithm for computing dynamically feasible actions with two higher level planners for generating long‐range plans in both on‐road and unstructured areas of the environment. In the first part of this article, we describe the underlying trajectory generator and the on‐road planning component of this system. We then describe the unstructured planning component of this system used for navigating through parking lots and recovering from anomalous on‐road scenarios. Throughout, we provide examples and results from “Boss” an autonomous sport utility vehicle that has driven itself over 3,000 km and competed in, and won, the DARPA Urban Challenge. © 2008 Wiley Periodicals, Inc.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
