Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion

通过智能传感器数据融合避免航线碰撞

• 批准号: LP200301507
• 负责人: Prof Ba-Ngu Vo
• 金额: $ 28.43万
• 依托单位: Curtin University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2022
• 资助国家: 澳大利亚
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP200301507
• 关键词: Collision; Avoidance; Shipping; Lanes; via

This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed methodology enables quantification of confidence in the predictions. This will provide ship owners, directly to their vessels and/or at the fleet management centres, information such as weather reports, reliable collision/no-collision warnings and avoidance strategies, on-the-fly.

该项目旨在开发一个在线海上交通监测系统，利用高分辨率机载传感器和水面船只传感器提供的补充数据，可靠地避免碰撞/接触。我们的方法是基于最佳的调度和融合的传感器数据和可能的其他来源的数据，以构建一个全面的动态图片的海上交通，实时。此外，所提出的方法能够量化预测的置信度。这将直接向船东和/或船队管理中心提供信息，如天气报告、可靠的碰撞/非碰撞警告和避免策略。