Abstract
Collision avoidance and risk assessment are open problems to be practically addressed in maritime transportation. In high-speed vessels this problem becomes more challenging due to manoeuvring and reaction time constraints. Here, a reactive collision avoidance and risk assessment technique with fuzzy weighting functions are proposed for a relatively high-speed autonomous catamaran. To follow paths between predefined waypoints, a Line of Sight (LOS) technique with Cross Tracking Error (CTE) is utilised. Besides, a new collision risk index is introduced based on fuzzy weighting functions. To perform formal maritime decision making, the standard marine COLlision REGulations (COLREGs) are incorporated into the algorithm. Furthermore, a simplified Closest Point of Approach (CPA) formulation is presented. The proposed framework is simulated on a realistic model of a vessel including input and non-holonomic constraints and disturbances. Simulation results for various encounter scenarios demonstrate the merits of the proposed method.
Original language | English |
---|---|
Title of host publication | CONTROL 2022: The 13th UK Automatic Control Council (UKACC) International Conference |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 228-234 |
Number of pages | 7 |
ISBN (Print) | 978-1-6654-5201-4 |
DOIs | |
Publication status | Published - 22 Apr 2022 |
Event | CONTROL 2022: The 13th UK Automatic Control Council (UKACC) International Conference - University of Plymouth, Plymouth, United Kingdom Duration: 20 Apr 2022 → 22 Apr 2022 https://events.imeche.org/ViewEvent?code=CMP7459 |
Conference
Conference | CONTROL 2022: The 13th UK Automatic Control Council (UKACC) International Conference |
---|---|
Country/Territory | United Kingdom |
City | Plymouth |
Period | 20/04/22 → 22/04/22 |
Internet address |
Keywords
- Machine learning algorithms
- Simulation
- Transportation
- Machine learning
- Regulation
- Risk management
- Indexes