Data/Knowledge-Driven Behaviour Analysis for Maritime Autonomous Surface Ships

• Andere auteurs: Wen, Yuanqiao (Redacteur), Hahn, Axel (Redacteur), Valdez Banda, Osiris (Redacteur), Huang, Yamin (Redacteur)
• Formaat: Elektronisch Hoofdstuk
• Taal: Engels
• Gepubliceerd in: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
• Onderwerpen: Technology: general issues; History of engineering & technology; Transport technology & trades; unmanned surface vehicle; velocity obstacle; collision avoidance; obstacles classification; fuzzy rules; mixed waterborne traffic; ship behavior; ship autonomy; information perception; intelligent decision-making; execution; COLREGs; ship object; formal expression; complex waters; ship traffic flow; spatiotemporal dependence; gate recurrent unit; motion planning; unmanned surface vehicle (USV); effects of wind and current; regularization-trajectory cell; inland waterway transportation; AIS data; trajectory classification; clustering; deep convolutional neural network; ship intention identification; AIS; RANSAC; Bayesian framework; YOLO; intersection; maritime autonomous surface ships; hybrid causal logic; preliminary hazard analysis; risk assessment; hazard identification; autonomous ship; ship manoeuvrability; deduction of the manoeuvring process; ship exhaust behavior; detection and tracking; multi-sensor; deep learning; morphological operation; collision alert system (CAS); available maneuvering margins (AMM); ship domain; ship stability; maritime safety; semantic modeling; cognitive space; multi-scale analysis; ontology; n/a
• Online toegang: DOAB: download the publication; DOAB: description of the publication

Maritime traffic data (e.g., radar data, AIS data, and CCTV data) provide designers, officers on watch, and traffic operators with extensive information about the states of ships at present and in history, representing a treasure trove for behavior analysis. Additionally, navigation rules and regula...