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Safe Trajectory Synthesis for Autonomous Driving in Unforeseen Environments

[+] Author Affiliations
Shreyas Kousik, Sean Vaskov, Matthew Johnson-Roberson, Ram Vasudevan

University of Michigan, Ann Arbor, MI

Paper No. DSCC2017-5361, pp. V001T44A005; 10 pages
doi:10.1115/DSCC2017-5361
From:
  • ASME 2017 Dynamic Systems and Control Conference
  • Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Control; Adaptive and Intelligent Systems Control; Advances in Wind Energy Systems; Advances in Robotics; Assistive and Rehabilitation Robotics; Biomedical and Neural Systems Modeling, Diagnostics, and Control; Bio-Mechatronics and Physical Human Robot; Advanced Driver Assistance Systems and Autonomous Vehicles; Automotive Systems
  • Tysons, Virginia, USA, October 11–13, 2017
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5827-1
  • Copyright © 2017 by ASME

abstract

Path planning for autonomous vehicles in arbitrary environments requires a guarantee of safety, but this can be impractical to ensure in real-time when the vehicle is described with a high-fidelity model. To address this problem, this paper develops a method to perform trajectory design by considering a low-fidelity model that accounts for model mismatch. The presented method begins by computing a conservative Forward Reachable Set (FRS) of a high-fidelity model’s trajectories produced when tracking trajectories of a low-fidelity model over a finite time horizon. At runtime, the vehicle intersects this FRS with obstacles in the environment to eliminate trajectories that can lead to a collision, then selects an optimal plan from the remaining safe set. By bounding the time for this set intersection and subsequent path selection, this paper proves a lower bound for the FRS time horizon and sensing horizon to guarantee safety. This method is demonstrated in simulation using a kinematic Dubin’s car as the low-fidelity model and a dynamic unicycle as the high-fidelity model.

Copyright © 2017 by ASME

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