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dc.contributor.authorWoerner, Kyle
dc.contributor.authorBenjamin, Michael
dc.contributor.authorNovitzky, Michael
dc.contributor.authorLeonard, John J
dc.date.accessioned2018-06-13T19:55:09Z
dc.date.available2018-06-13T19:55:09Z
dc.date.issued2018-05
dc.identifier.issn0929-5593
dc.identifier.issn1573-7527
dc.identifier.urihttp://hdl.handle.net/1721.1/116295
dc.description.abstractCollision avoidance protocols such as COLREGS are written primarily for human operators resulting in a rule set that is open to some interpretation, difficult to quantify, and challenging to evaluate. Increasing use of autonomous control of vehicles emphasizes the need to more uniformly establish entry and exit criteria for collision avoidance rules, adopt a means to quantitatively evaluate performance, and establish a “road test” for autonomous marine vehicle collision avoidance. This paper presents a means to quantify and subsequently evaluate the otherwise subjective nature of COLREGS thus providing a path toward standardized evaluation and certification of protocol-constrained collision avoidance systems based on admiralty case law and on-water experience. Notional algorithms are presented for evaluation of COLREGS collision avoidance rules to include overtaking, head-on, crossing, give-way, and stand-on rules as well as applicable entry criteria. These rules complement and enable an autonomous collision avoidance road test as a first iteration of algorithm certification prior to vessels operating in human-present environments. Additional COLREGS rules are discussed for future development. Both real-time and post-mission protocol evaluation tools are introduced. While the motivation of these techniques applies to improvement of autonomous marine collision avoidance, the concepts for protocol evaluation and certification extend naturally to human-operated vessels. Evaluation of protocols governing other physical domains may also benefit from adapting these techniques to their cases. Keywords: COLREGS; Autonomous collision avoidance; Human–robot collaboration; Marine navigationen_US
dc.language.isoen_US
dc.publisherSpringer-Verlagen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s10514-018-9765-yen_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceWoerneren_US
dc.titleQuantifying protocol evaluation for autonomous collision avoidanceen_US
dc.typeArticleen_US
dc.identifier.citationWoerner, Kyle et al. “Quantifying Protocol Evaluation for Autonomous Collision Avoidance.” Autonomous Robots (May 2018): 1-25 © 2018 Springer Science+Business Media, LLC, part of Springer Natureen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.approverWoerner, Kyleen_US
dc.contributor.mitauthorWoerner, Kyle
dc.contributor.mitauthorBenjamin, Michael
dc.contributor.mitauthorNovitzky, Michael
dc.contributor.mitauthorLeonard, John J
dc.relation.journalAutonomous Robotsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsWoerner, Kyle; Benjamin, Michael R.; Novitzky, Michael; Leonard, John J.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-9499-9630
dc.identifier.orcidhttps://orcid.org/0000-0002-1854-9750
dc.identifier.orcidhttps://orcid.org/0000-0002-8863-6550
mit.licenseOPEN_ACCESS_POLICYen_US


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