DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ren, Kai | ko |
dc.contributor.author | Ahn, Heejin | ko |
dc.contributor.author | Kamgarpour, Maryam | ko |
dc.date.accessioned | 2022-11-18T08:00:15Z | - |
dc.date.available | 2022-11-18T08:00:15Z | - |
dc.date.created | 2022-11-18 | - |
dc.date.created | 2022-11-18 | - |
dc.date.issued | 2022-06 | - |
dc.identifier.citation | IEEE CONTROL SYSTEMS LETTERS, v.7, pp.13 - 18 | - |
dc.identifier.issn | 2475-1456 | - |
dc.identifier.uri | http://hdl.handle.net/10203/300085 | - |
dc.description.abstract | We tackle safe trajectory planning under Gaussian mixture model (GMM) uncertainty. Specifically, we use a GMM to model the multimodal behaviors of obstacles’ uncertain states. Then, we develop a mixed-integer conic approximation to the chance-constrained trajectory planning problem with deterministic linear systems and polyhedral obstacles. When the GMM moments are estimated via finite samples, we develop a tight concentration bound to ensure the chance constraint with a desired confidence. Moreover, to limit the amount of constraint violation, we develop a Conditional Value-at-Risk (CVaR) approach corresponding to the chance constraints and derive a tractable approximation for known and estimated GMM moments. We verify our methods with state-of-the-art trajectory prediction algorithms and autonomous driving datasets. | - |
dc.language | English | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Chance-Constrained Trajectory Planning With Multimodal Environmental Uncertainty | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 7 | - |
dc.citation.beginningpage | 13 | - |
dc.citation.endingpage | 18 | - |
dc.citation.publicationname | IEEE CONTROL SYSTEMS LETTERS | - |
dc.identifier.doi | 10.1109/lcsys.2022.3186269 | - |
dc.contributor.localauthor | Ahn, Heejin | - |
dc.contributor.nonIdAuthor | Ren, Kai | - |
dc.contributor.nonIdAuthor | Kamgarpour, Maryam | - |
dc.description.isOpenAccess | N | - |
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