Safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs
Author(s)McNew, John M.; Forghani Oozroody, Mojtaba; Hoehener, Daniel Andreas; Del Vecchio, Domitilla
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In this paper, we consider the problem of keeping the state of a system outside of an undesired set of states with probability at least P. We focus on a class of order preserving systems with a constant input disturbance that is extracted from a known probability distribution. Leveraging the structure of the system, we construct an explicit supervisor that guarantees the system state to be kept outside the undesired set with at least probability P. We apply this supervisor to a collision avoidance problem, where a semi-autonomous vehicle is engaged in preventing a rear-end collision with a preceding human-driven vehicle, while stopping at a stop sign. We apply the designed supervisor in simulations in which the preceding vehicle trajectories are taken from a test data set. Using this data, we demonstrate experimentally that the probability of preventing a rear-end collision while stopping at the stop sign is at least P, as expected from theory. The simulation results further show that this probability is very close to P, indicating that the supervisor is not conservative.
DepartmentMassachusetts Institute of Technology. Department of Mechanical Engineering
American Control Conference (ACC), 2015
Institute of Electrical and Electronics Engineers (IEEE)
Forghani, Mojtaba, John M. McNew, Daniel Hoehener, and Domitilla Del Vecchio. “Safety Control of a Class of Stochastic Order Preserving Systems with Application to Collision Avoidance Near Stop Signs.” 2015 American Control Conference (ACC) (July 2015), Chicago, IL, USA, Institute of Electrical and Electronics Engineers (IEEE), 2015.
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