Enhanced Underwater AIS for Communication-Based Collision Avoidance in Autonomous Underwater Vehicles

The increasing complexity of underwater environments due to expanding marine research, exploration, and industrial activities has elevated the collision risk for autonomous underwater vehicles (AUVs).Traditional sensor-based collision avoidance (COLAV) systems can be constrained by environmental factors such as acoustic noise and low visibility, prompting more robust solutions.One promising approach is data sharing via the JANUS-based Underwater AIS (UAIS) protocol.UAIS could also inform decision-making when making underwater COLREG-compliant systems.This paper proposes several UAIS enhancements-including fields for uncertainty and manoeuvrability, dynamic data transmission, and hybrid acoustic-optical communication-and addresses associated security needs using encryption and authentication measures.To quantify UAIS's potential impact, two Bayesian Networks (BNs) estimate how UAIS data can reduce an AUV's risk of losing navigational control.Results suggest a notable drop in collision risk when UAIS is integrated.Nonetheless, challenges remain regarding cost, standardization, and the possibility of overreliance on AIS data.The proposed system marks a promising step toward safer and more efficient underwater navigation through communication-based COLAV solutions.