Results 31 to 40 of about 2,001 (213)
A Novel Adaptive Visual Analytics Framework for Multiship Encounter Identification
Journal of Advanced Transportation, Volume 2021, Issue 1, 2021., 2021 The automatic identification of multiship encounter is a vital criterion for ship collision avoidance and intelligent maritime safety surveillance. However, the parameters of ship encounter identification in the existing studies are fixed, and the methods are weak to give an automatic and visual performance in the multiship encounter identification. In
Rong Zhen, Ziqiang Shi, Xinqiang Chen
wiley +1 more source
Survey on Deep Learning‐Based Marine Object Detection
Journal of Advanced Transportation, Volume 2021, Issue 1, 2021., 2021 We present a survey on marine object detection based on deep neural network approaches, which are state‐of‐the‐art approaches for the development of autonomous ship navigation, maritime surveillance, shipping management, and other intelligent transportation system applications in the future.
Ruolan Zhang +6 more
wiley +1 more source
Journal of Marine Science and Engineering, 2021 The collision avoidance system is one of the core systems of MASS (Maritime Autonomous Surface Ships). The collision avoidance system was validated using scenario-based experiments. However, the scenarios for the validation were designed based on COLREG (
Taewoong Hwang, Ik-Hyun Youn
doaj +1 more source
An Ordinal Model of Risk Based on Mariner’s Judgement [PDF]
, 2016 This paper describes a statistical method for learning and estimating the risk posed by other craft in the vicinity of a vessel and an overview of its possible spatial application, simulating how professional mariners perceive and assess such risk and ...
Lawry, Jonathan, Lopez-Santander, Adan
core +2 more sources
Journal of Robotics, Volume 2021, Issue 1, 2021., 2021 The bacterial foraging optimization algorithm (BFOA) is an intelligent population optimization algorithm widely used in collision avoidance problems; however, the BFOA is inappropriate for the intelligent ship collision avoidance planning with high safety requirements because BFOA converges slowly, optimizes inaccurately, and has low stability.
Xingzhong Wang +4 more
wiley +1 more source
Journal of Advanced Transportation, Volume 2021, Issue 1, 2021., 2021 Maritime Autonomous Surface Ships (MASSs) are attracting increasing attention in recent years as it brings new opportunities for water transportation. Previous studies aim to propose fully autonomous system on collision avoidance decisions and operations, either focus on supporting conflict detection or providing with collision avoidance decisions ...
Xiaolie Wu +6 more
wiley +1 more source
Design of obstacle detection and avoidance system for GUANAY II AUV [PDF]
, 2016 Postprint (published ...
Galarza Bogotá, Cesar Mauricio +3 more
core +1 more source
A Decision‐Making Method for Ship Collision Avoidance Based on Improved Cultural Particle Swarm
Journal of Advanced Transportation, Volume 2021, Issue 1, 2021., 2021 In the process of ship collision avoidance decision making, steering collision avoidance is the most frequently adopted collision avoidance method. In order to obtain an effective and reasonable steering angle, this paper proposes a decision‐making method for ship collision avoidance based on improved cultural particle swarm. Firstly, the ship steering
Yisong Zheng +5 more
wiley +1 more source
COLREG-Compliant Collision Avoidance for Unmanned Surface Vehicle Using Deep Reinforcement Learning
IEEE Access, 2020 Path Following and Collision Avoidance, be it for unmanned surface vessels or other autonomous vehicles, are two fundamental guidance problems in robotics.
Eivind Meyer +3 more
doaj +1 more source
Journal of Marine Science and Engineering, 2023 The increasing traffic and complexity of navigation at sea require advanced decision support systems to ensure greater safety. In this study, we propose a novel decision support system that employs fuzzy logic to improve situational awareness and to ...
Tanja Brcko, Blaž Luin
doaj +1 more source