Distributed MPC for autonomous ships on inland waterways with collaborative collision avoidance

This paper presents a distributed solution for the problem of collaborative collision avoidance for autonomous inland waterway ships. A two-layer collision avoidance framework that considers inland waterway traffic regulations is proposed to increase navigational safety for autonomous ships. Our approach allows for modifying traffic rules without changing the collision avoidance algorithm, which is based on a novel formulation of model predictive control (MPC) for collision avoidance of ships. This MPC formulation is designed for inland waterway traffic and can handle complex scenarios. The alternating direction method of multipliers (ADMM) is used as a scheme for exchanging and negotiating intentions among ships. Simulation results demonstrate that the proposed algorithm enables ships to avoid collisions with a sufficient margin while adhering to traffic rules. Furthermore, the proposed algorithm can safely deviate from traffic rules when necessary to increase traffic efficiency in complex scenarios.