TY - JOUR
T1 - A method to identify and rank objects and hazardous interactions affecting autonomous ships navigation
AU - Bolbot, Victor
AU - Theotokatos, Gerasimos
AU - Wennersberg, Lars Andreas
N1 - Funding Information:
The study was carried out in the framework of the AUTOSHIP project (AUTOSHIP, 2019), which is funded by the European Union's Horizon 2020 research and innovation programme under agreement No. 815012. The authors affiliated with the Maritime Safety Research Centre (MSRC) greatly acknowledge the funding from DNV AS and RCCL for the establishment and operation of the MSRC. The authors also thank the and individuals from Eidsvaag and Kongsberg Maritime for their comments. The opinions expressed herein are those of the authors and should not be construed to reflect the views of EU, DNV AS, RCCL, Eidsvaag, Kongsberg Maritime or other involved partners in the AUTOSHIP project.
Publisher Copyright:
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of The Royal Institute of Navigation.
PY - 2022/5
Y1 - 2022/5
N2 - 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.
AB - 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.
KW - autonomous navigation
KW - autonomous ships
KW - environmental complexity
KW - safety requirements
KW - targets identification
UR - http://www.scopus.com/inward/record.url?scp=85129285491&partnerID=8YFLogxK
U2 - 10.1017/S0373463322000121
DO - 10.1017/S0373463322000121
M3 - Article
AN - SCOPUS:85129285491
SN - 0373-4633
VL - 75
SP - 572
EP - 593
JO - JOURNAL OF NAVIGATION
JF - JOURNAL OF NAVIGATION
IS - 3
M1 - 0373463322000121
ER -