Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorGil, Mateuszen_US
dc.contributor.authorKozioł, Pawełen_US
dc.contributor.authorWróbel, Krzysztofen_US
dc.contributor.authorMontewka, Jakuben_US
dc.contributor.departmentDepartment of Energy and Mechanical Engineeringen
dc.contributor.groupauthorMarine Technologyen
dc.contributor.organizationWaterborne Transport Innovationen_US
dc.contributor.organizationGdynia Maritime Universityen_US
dc.date.accessioned2022-01-12T07:19:01Z
dc.date.available2022-01-12T07:19:01Z
dc.date.issued2022-04en_US
dc.descriptionFunding Information: The study described has been performed as part of the Detection, prediction, and solutions for safe operations of MASS (ENDURE) project (number NOR/POLNOR/ENDURE/0019/2019–00), supported by the Polish National centre for Research and Development and financed by Research Council of Norway. The authors are grateful to Danish Maritime Authority for making the AIS data available for analysis. Funding Information: The study described has been performed as part of the Detection, prediction, and solutions for safe operations of MASS (ENDURE) project (number NOR/POLNOR/ENDURE/0019/2019?00), supported by the Polish National centre for Research and Development and financed by Research Council of Norway. The authors are grateful to Danish Maritime Authority for making the AIS data available for analysis. Publisher Copyright: © 2021 The Author(s)
dc.description.abstractEven in the era of automatization maritime safety constantly needs improvements. Regardless of the presence of crew members on board, both manned and autonomous ships should follow clear guidelines (no matter as bridge procedures or algorithms). To date, many safety indicators, especially in collision avoidance have been proposed. One of such parameters commonly used in day-to-day navigation but usually omitted by researchers is Bow Crossing Range (BCR). Therefore, this paper aims to investigate, what are typical, empirical values of BCR during routine operations of merchant ships, as well as investigate what factors impact this indicator and to what extent. To this end, a ten-year big dataset of real maritime traffic obtained from the Automatic Identification System (AIS) was used to provide statistical and spatiotemporal analyses. The results indicate that BCR is strongly related to the type of navigational area (open sea or restricted waters) but not with the dimensions or speed of ships. Among analyzed vessel types, passenger ships were noted as vessels that cross other bows at the closes ranges. Results of this study may be found interesting by fleet managers and developers of Maritime Autonomous Surface Ships (MASS). The former could utilize the results to provide revised operational guidelines for deck officers while the latter - propose an early-detection warning system based on empirical data for prospective MASS.en
dc.description.versionPeer revieweden
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationGil, M, Kozioł, P, Wróbel, K & Montewka, J 2022, 'Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics', Reliability Engineering and System Safety, vol. 220, 108311. https://doi.org/10.1016/j.ress.2021.108311en
dc.identifier.doi10.1016/j.ress.2021.108311en_US
dc.identifier.issn0951-8320
dc.identifier.issn1879-0836
dc.identifier.otherPURE UUID: f659473d-266c-48d6-9794-0e246e643a79en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/f659473d-266c-48d6-9794-0e246e643a79en_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/78025164/1_s2.0_S095183202100781X_main.pdf
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/112279
dc.identifier.urnURN:NBN:fi:aalto-202201121187
dc.language.isoenen
dc.publisherElsevier
dc.relation.fundinginfoThe study described has been performed as part of the Detection, prediction, and solutions for safe operations of MASS (ENDURE) project (number NOR/POLNOR/ENDURE/0019/2019–00), supported by the Polish National centre for Research and Development and financed by Research Council of Norway. The authors are grateful to Danish Maritime Authority for making the AIS data available for analysis. The study described has been performed as part of the Detection, prediction, and solutions for safe operations of MASS (ENDURE) project (number NOR/POLNOR/ENDURE/0019/2019?00), supported by the Polish National centre for Research and Development and financed by Research Council of Norway. The authors are grateful to Danish Maritime Authority for making the AIS data available for analysis.
dc.relation.ispartofseriesReliability Engineering and System Safetyen
dc.relation.ispartofseriesVolume 220en
dc.rightsopenAccessen
dc.subject.keywordAutomatic Identification System (AIS)en_US
dc.subject.keywordbig data analysisen_US
dc.subject.keywordBow Crossing Range (BCR)en_US
dc.subject.keywordMaritime Autonomous Surface Ships (MASS)en_US
dc.subject.keywordmaritime risk and safetyen_US
dc.subject.keywordship collision avoidanceen_US
dc.titleKnow your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analyticsen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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