TY  - GEN
N2  - Autonomous maritime vessels have gained a considerable amount of attention in recent years due to their promise of reduced crew costs, increased safety and increased flexibility. This paper explores how the maritime industry can leverage the developments in autonomy and other systems to contribute to the continued drive towards autonomous maritime systems. First, several key technological areas associated with autonomous maritime systems are identified; including navigation and control systems, data transmission and electrical energy propulsion. These technical areas are then compared with other autonomous systems including autonomous aircraft, automobiles and spacecraft to find overlaps and similarities. A set of representative patents are determined for each technological area across each of the different autonomous systems and is then used to estimate a technological improvement rate for each technology-system pair. These technological improvement rates are implemented in a Monte-Carlo Markov Chain model to explore the effects of the timing of the adoption of autonomous systems in the maritime shipping industry. The model indicates a technological feasibility date of maritime autonomous systems beginning in 2028 when leveraging autonomous developments from other domains.
AB  - Autonomous maritime vessels have gained a considerable amount of attention in recent years due to their promise of reduced crew costs, increased safety and increased flexibility. This paper explores how the maritime industry can leverage the developments in autonomy and other systems to contribute to the continued drive towards autonomous maritime systems. First, several key technological areas associated with autonomous maritime systems are identified; including navigation and control systems, data transmission and electrical energy propulsion. These technical areas are then compared with other autonomous systems including autonomous aircraft, automobiles and spacecraft to find overlaps and similarities. A set of representative patents are determined for each technological area across each of the different autonomous systems and is then used to estimate a technological improvement rate for each technology-system pair. These technological improvement rates are implemented in a Monte-Carlo Markov Chain model to explore the effects of the timing of the adoption of autonomous systems in the maritime shipping industry. The model indicates a technological feasibility date of maritime autonomous systems beginning in 2028 when leveraging autonomous developments from other domains.
AD  - Delft University of Technology, Netherlands; United States Air Force Office of Scientific Research, United States; Massachusetts Institute of Technology, Cambridge, United States
AD  - Delft University of Technology, Netherlands
AD  - Delft University of Technology, Netherlands
T1  - Standing on the Shoulders of Giants: How the Maritime Industry can Leverage Developments in Autonomy from other Domains
DA  - 2018-10-02
AU  - Benson, C L
AU  - Sumanth, P D
AU  - Colling, A P
L1  - https://library.imarest.org/record/7572/files/INEC%202018%20Paper%20002%20Benson%20SDG%20FINAL.pdf
JF  - Conference Proceedings of INEC
VL  - INEC 2018
PY  - 2018-10-02
ID  - 7572
L4  - https://library.imarest.org/record/7572/files/INEC%202018%20Paper%20002%20Benson%20SDG%20FINAL.pdf
KW  - Autonomous Maritime
KW  - Technology Forecasting
KW  - Logistics Modelling
TI  - Standing on the Shoulders of Giants: How the Maritime Industry can Leverage Developments in Autonomy from other Domains
Y1  - 2018-10-02
L2  - https://library.imarest.org/record/7572/files/INEC%202018%20Paper%20002%20Benson%20SDG%20FINAL.pdf
LK  - https://www.imarest.org/inec
LK  - https://library.imarest.org/record/7572/files/INEC%202018%20Paper%20002%20Benson%20SDG%20FINAL.pdf
UR  - https://www.imarest.org/inec
UR  - https://library.imarest.org/record/7572/files/INEC%202018%20Paper%20002%20Benson%20SDG%20FINAL.pdf
ER  -