Real-Time Motion Planning With Applications to Autonomous Urban Driving
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This paper describes a real-time motion planning algorithm, based on the rapidly-exploring random tree (RRT) approach, applicable to autonomous vehicles operating in an urban environment. Extensions to the standard RRT are predominantly motivated by: 1) the need to generate dynamically feasible plans in real-time; 2) safety requirements; 3) the constraints dictated by the uncertain operating (urban) environment. The primary novelty is in the use of closed-loop prediction in the framework of RRT. The proposed algorithm was at the core of the planning and control software for Team MIT's entry for the 2007 DARPA Urban Challenge, where the vehicle demonstrated the ability to complete a 60 mile simulated military supply mission, while safely interacting with other autonomous and human driven vehicles.
Date issued
2009-08Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer ScienceJournal
IEEE Transactions on Control Systems Technology
Publisher
Institute of Electrical and Electronics Engineers
Citation
Kuwata, Y. et al. “Real-Time Motion Planning With Applications to Autonomous Urban Driving.” Control Systems Technology, IEEE Transactions on 17.5 (2009): 1105-1118. © 2009 Institute of Electrical and Electronics Engineers
Version: Final published version
Other identifiers
INSPEC Accession Number: 10841689
ISSN
1063-6536
Keywords
urban driving, real-time motion planning, rapidly-exploring random tree (RRT), dynamic and uncertain environment, DARPA urban challenge, autonomous