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Bolbot, V, Theotokatos, G and Wennersberg, LA (2022) A method to identify and rank objects and hazardous interactions affecting autonomous ships navigation. Journal of Navigation, 75 (3). pp. 572-593. ISSN 0373-4633
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Abstract
The Autonomous Navigation System (ANS) constitutes a critical key enabling technology required for operating Maritime Autonomous Surface Ships (MASS). To assure the safety of MASS operations, the effective identification of potential objects and target ships interacting with the own MASS is quintessential. This study proposes a systematic method to identify the items interacting with the own MASS. This method is based on a similar approach previously employed for the encountering items' identification in robotics, which is customised herein for the MASS needs. The developed method is applied to a short-sea shipping MASS. The environmental features, agents and objects related to her navigation are identified and ranked based on the frequency of encounter and the potential collision consequences. The results demonstrate the ability of the method to identify additional items in comparison to Automatic Identification System based data. The interactions with the small ships are considered as the most critical, due to their potential accidental consequences and their exhibited high frequency of encounter. This study results are employed to support the ANS design and testing of the investigated ship.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 0909 Geomatic Engineering; Logistics & Transportation; 0909 Geomatic Engineering; Logistics & Transportation |
| Subjects: | H Social Sciences > HE Transportation and Communications T Technology > TA Engineering (General). Civil engineering (General) V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering |
| Divisions: | Engineering |
| Publisher: | Cambridge University Press (CUP) |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 14 Dec 2022 10:44 |
| Last Modified: | 14 Dec 2022 10:44 |
| DOI or ID number: | 10.1017/S0373463322000121 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/18390 |
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