Enabling autonomous navigation: adaptive multi-source risk quantification in maritime transportation
提出一种基于AIS数据的自适应多源风险量化框架，整合船舶动态与静态环境风险，提升复杂场景下导航风险评估精度，为自主导航和智能海事系统提供支持。
• Design a spatiotemporal risk model based on AIS data for maritime risk prediction. • Develop risk functions to account for navigation hazard sensitivity. • Propose adaptive risk quantification for early maritime warnings. • Establish a fusion model to combine diverse navigation risks. • Validate the framework with real data to analyse maritime risk scenarios. Current studies on maritime navigation risks often overlook interactions between ships, dynamic surroundings, and static environmental factors, limiting insights into navigation safety in complex scenarios. This research presents an innovative methodology to quantify and integrate multi-source heterogeneous navigation risks, enabling a comprehensive assessment of overall risk levels. The framework comprises four components. First, a spatiotemporal risk monitoring domain model, developed using historical AIS data, incorporates risk monitoring and forbidden domains, enabling precise localisation and timing of risk evaluation. Second, heterogeneous navigation risk evaluation functions, addressing dynamic target and static environment risks, capture ships’ varying sensitivities to diverse risk sources. Third, risk quantification methods evaluate dynamic risks from temporal and spatial perspectives while categorising static risks into three types. Finally, an adaptive fusion method hierarchically aggregates multi-source risk data into a unified profile, reflecting navigators’ risk perception. Real-world AIS data validate the framework, constructing spatiotemporal risk models for three ship types and analysing navigation scenarios such as crossing, overtaking, and multi-ship encounters. Results demonstrate the framework's capability to enhance precision in navigation risk assessment, providing actionable insights and robust support for autonomous navigation and intelligent maritime systems. This methodology offers a promising tool for advancing safety in complex maritime environments.