Print Email Facebook Twitter Parallel autonomy in automated vehicles Title Parallel autonomy in automated vehicles: Safe motion generation with minimal intervention Author Schwarting, Wilko (Massachusetts Institute of Technology) Alonso Mora, J. (TU Delft Learning & Autonomous Control) Pauli, Liam (Massachusetts Institute of Technology) Karaman, Sertac (Massachusetts Institute of Technology) Rus, Daniela (Massachusetts Institute of Technology) Contributor Chen, I-Ming (editor) Nakamura, Yoshihiko (editor) Date 2017 Abstract Current state-of-the-art vehicle safety systems, such as assistive braking or automatic lane following, are still only able to help in relatively simple driving situations. We introduce a Parallel Autonomy shared-control framework that produces safe trajectories based on human inputs even in much more complex driving scenarios, such as those commonly encountered in an urban setting. We minimize the deviation from the human inputs while ensuring safety via a set of collision avoidance constraints. We develop a receding horizon planner formulated as a Non-linear Model Predictive Control (NMPC) including analytic descriptions of road boundaries, and the configurations and future uncertainties of other traffic participants, and directly supplying them to the optimizer without linearization. The NMPC operates over both steering and acceleration simultaneously. Furthermore, the proposed receding horizon planner also applies to fully autonomous vehicles. We validate the proposed approach through simulations in a wide variety of complex driving scenarios such as left-turns across traffic, passing on busy streets, and under dynamic constraints in sharp turns on a race track. Subject VehiclesRoadsOptimizationSafetyAccelerationTrajectoryUncertainty To reference this document use: http://resolver.tudelft.nl/uuid:1b9f5841-7e60-4d45-a430-08a2924fcd75 DOI https://doi.org/10.1109/ICRA.2017.7989224 Publisher IEEE, Piscataway, NJ, USA ISBN 978-1-5090-4633-1 Source Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2017) Event 2017 IEEE International Conference on Robotics and Automation, ICRA 2017, 2017-05-29 → 2017-06-03, Singapore, Singapore Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type conference paper Rights © 2017 Wilko Schwarting, J. Alonso Mora, Liam Pauli, Sertac Karaman, Daniela Rus Files PDF 110365_10.pdf 1.67 MB Close viewer /islandora/object/uuid:1b9f5841-7e60-4d45-a430-08a2924fcd75/datastream/OBJ/view