Abstract
The objective of this article is to present a method for developing collision risk indicators applicable for autonomous remotely operated vehicles (AROVs), which are essential for promoting situation awareness in decisions support systems. Three suitable risk based collision indicators are suggested for AROVs namely, time to collision, mean time to collision and mean impact energy. The proposed indicators are classified into different thresholds; low, intermediate and high. An AROV flight path is simulated to gather input data to calculate the proposed indicators and three collision targets are established, i.e., subsea structure, seabed and a cooperating AROV. The proposed indicator development method together with the case study show a proof-of-concept that the combination of mean time to collision and mean impact energy indicators can identify risk prone waypoints in the AROV path. The method results in an overall risk picture for a given AROV path. The results may provide useful input in replanning of mission paths and for implementation of risk reducing measures. Even though the method focuses on collision risk, it can be used for other accident scenarios for AROVs.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Loss Prevention in the Process Industries
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
