Safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs
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 structu...
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| Format: | Article |
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Institute of Electrical and Electronics Engineers (IEEE)
2018
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| Online Access: | http://hdl.handle.net/1721.1/119210 https://orcid.org/0000-0001-8695-1891 https://orcid.org/0000-0003-1866-6970 https://orcid.org/0000-0001-6472-8576 |
| _version_ | 1811081142060711936 |
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| author | McNew, John M. Forghani Oozroody, Mojtaba Hoehener, Daniel Andreas Del Vecchio, Domitilla |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering McNew, John M. Forghani Oozroody, Mojtaba Hoehener, Daniel Andreas Del Vecchio, Domitilla |
| author_sort | McNew, John M. |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T11:42:09Z |
| format | Article |
| id | mit-1721.1/119210 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:42:09Z |
| publishDate | 2018 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1192102022-09-27T21:21:13Z Safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs McNew, John M. Forghani Oozroody, Mojtaba Hoehener, Daniel Andreas Del Vecchio, Domitilla Massachusetts Institute of Technology. Department of Mechanical Engineering Forghani Oozroody, Mojtaba Hoehener, Daniel Andreas Del Vecchio, Domitilla 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. National Science Foundation (U.S.) (award #1161893) 2018-11-19T19:46:59Z 2018-11-19T19:46:59Z 2015-07 2018-11-09T18:24:42Z Article http://purl.org/eprint/type/ConferencePaper 978-1-4799-8684-2 978-1-4799-8685-9 0743-1619 2378-5861 http://hdl.handle.net/1721.1/119210 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. https://orcid.org/0000-0001-8695-1891 https://orcid.org/0000-0003-1866-6970 https://orcid.org/0000-0001-6472-8576 http://dx.doi.org/10.1109/ACC.2015.7170786 American Control Conference (ACC), 2015 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) MIT Web Domain |
| spellingShingle | McNew, John M. Forghani Oozroody, Mojtaba Hoehener, Daniel Andreas Del Vecchio, Domitilla Safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs |
| title | Safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs |
| title_full | Safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs |
| title_fullStr | Safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs |
| title_full_unstemmed | Safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs |
| title_short | Safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs |
| title_sort | safety control of a class of stochastic order preserving systems with application to collision avoidance near stop signs |
| url | http://hdl.handle.net/1721.1/119210 https://orcid.org/0000-0001-8695-1891 https://orcid.org/0000-0003-1866-6970 https://orcid.org/0000-0001-6472-8576 |
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