On the Estimation of Mission Performance Index of Unmanned Surface Vehicle Based on Mission Coverage

Abstract

As unmanned automation technology has been developed very rapidly with the waves of the 4th industrial revolution, drones and self-driving vehicles have been commercialized. In the maritime domain, the operation concepts and navigation regulations of maritime autonomous surface ships (MASS) and unmanned surface vehicles (USV) have been reviewed in the international maritime organization (IMO). Especially, USV has longer operation time and larger payload than drone, so it is more useful for maritime missions such as sea surveillance, marine survey and life-saving, which have been conducted by manned ships. Because it is possible to increase the efficiency of maritime mission by operating multiple USVs rather than a single USV, many researches on the USV swarm for maritime missions have been conducted. When operating multiple USVs, it is necessary to monitor the mission efficiency of each USV for the re-plan of the route. For this, it is necessary to estimate the real-time mission efficiency of the USV. In this study, a mission performance index (MPI) is defined to estimate the mission efficiency of multiple USVs by using mission coverage area. When multiple USVs perform the maritime missions of sea surveillance such as illegal ship chasing maneuvers, the path followings of USVs are required on the illegal ship’s route. Therefore, MPI is estimated on the path following of each USV. MPI is real-timely calculated as the ratio of the individual mission area of the path following coverage, which is performed by the USV to the total area of mission coverage in the game area. In order to evaluate the performance of MPI, USV simulation has been carried out on the scenario of maritime mission of illegal ship chasing maneuvers. In this paper, MPI modeling and the results of USV simulation are introduced.