CrossRef Text and Data Mining
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Quantitative Evaluation of the Collision-Avoidance Capability of Maritime Autonomous Surface Ships Using FMSS
Seok-Han Bae, Min Jung, Eun-Kyu Jang
J Navig Port Res. 2020;44(6):460-468.   Published online December 31, 2001
DOI: https://doi.org/10.5394/KINPR.2020.44.6.460

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Local Route Planning for Collision Avoidance of Maritime Autonomous Surface Ships in Compliance with COLREGs Rules
Sustainability. 2021;14(1):198   Crossref logo
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Collision avoidance on maritime autonomous surface ships: Operators’ tasks and human failure events
Safety Science. 2019;116:33-44   Crossref logo
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Collision Avoidance Systems for Maritime Autonomous Surface Ships Considering Uncertainty in Ship Dynamics
IFAC-PapersOnLine. 2020;53(2):14614-14619   Crossref logo
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Survey on Collision-Avoidance Navigation of Maritime Autonomous Surface Ships
Offshore Robotics. 2021;1-33   Crossref logo
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Motion Plan of Maritime Autonomous Surface Ships by Dynamic Programming for Collision Avoidance and Speed Optimization
Sensors. 2019;19(2):434   Crossref logo
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Navigation Situation Clustering Model of Human-Operated Ships for Maritime Autonomous Surface Ship Collision Avoidance Tests
Journal of Marine Science and Engineering. 2021;9(12):1458   Crossref logo
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Collision Risk Inference System for Maritime Autonomous Surface Ships Using COLREGs Rules Compliant Collision Avoidance
IEEE Access. 2021;9:7823-7835   Crossref logo
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Collision risk measure for triggering evasive actions of maritime autonomous surface ships
Safety Science. 2020;127:104708   Crossref logo
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Comments to the article by Ramos et al. ‘Collision avoidance on maritime autonomous surface ships: Operators’ tasks and human failure events’ (Safety Science Vol. 116, July 2019, pp. 33–44)
Safety Science. 2020;121:603-605   Crossref logo
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Ship Collision Avoidance Using Scenario-Based Model Predictive Control**This work was supported by the Research Council of Norway, Statoil, DNV GL and Sintef through the Centers of Excellence funding scheme, Project number 223254 - Centre for Autonomous Marine Operations and Systems (NTNU-AMOS), and the Research Council of Norway, DNV GL, Kongsberg Maritime and Maritime Robotics through the MAROFF knowledge project 244116 Sensor Fusion and Collision Avoidance for Autonomous Surface Vessels.
IFAC-PapersOnLine. 2016;49(23):14-21   Crossref logo
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