This article focuses on the problem of collaborative collision avoidance (CCAS) for autonomous inland ships. Two solutions are provided to solve the problem in a distributed manner. We first present a distributed model predictive control (MPC) algorithm that allows ships to directly negotiate their intention to avoid collision in a synchronous communication framework. Moreover, we introduce a new approach to shape the ship’s behavior to follow the waterway traffic regulations. The conditional convergence toward a stationary solution of this algorithm is guaranteed by the theory of the alternating direction method of multipliers (ADMM). To overcome the problem of asynchronous communication between ships, we adopt a new asynchronous nonlinear ADMM (Async-NADMM) and present an asynchronous distributed MPC algorithm based on it. Several simulations and field experiments show that the proposed algorithms can guarantee a safe distance between ships in complex scenarios while following the traffic regulations. Furthermore, the asynchronous algorithm has an efficient computational time and satisfies the real-time computing requirements of ships in field experiments.

This paper presents an approach to the problem of collaborative collision avoidance of autonomous inland ships. We propose a distributed model predictive control algorithm that allows ships to negotiate their intention to collaboratively avoid collisions directly. Furthermore, a new method is introduced to better shape ships' behavior in order to follow Traffic regulations. The simulation results illustrate that the proposed algorithm could significantly increase ship safety navigation. Moreover, it also shows that the solution proposed by our algorithm complies with waterway Traffic regulations except in complex situations when other safe solutions are negotiated.

Collision avoidance is one of the most challenging problems in developing a Maritime Autonomous Surface Ship. This paper proposes a pro-active collision avoidance algorithm for inland waterway ships. The algorithm addresses the problem of avoiding collisions with dynamic obstacles by applying a situation-based intention prediction for neighboring ships. This prediction algorithm allows own ship to be aware of future collision threats caused by the course changes of nearby ships. The prediction scheme is integrated into a scenario-based model predictive control scheme that has been modified for application in inland waterway traffic. The proposed algorithm can deal with complex traffic situations that a ship can encounter, and the performance of the proposed algorithm is evaluated in several experiment simulations.

Promoting autonomous surface ships in inland waterways traffic (IWT) is a potential solution towards reducing road traffic and transport emission footprints. Over the last decade, there has been a growing research on autonomous ships for open waters. However, applying this research to the IWT domain is not straightforward. The IWT, due to its confined waterways, poses a different challenge than the open sea case. Due to the confined waterways, inland ships face several hydrodynamic phenomena that they rarely encountered in the open sea, such as shallow water, banks, or ship-to-ship effects. Furthermore, the higher traffic density in inland waterways also requires a different solution for sensing and control systems. This paper offers an overview of the current developments on autonomous collision avoidance for inland waterway ships that covering different problems of safety navigation for ship in IWT. A short analysis is presented to highlight the strengths and weaknesses of each approach. We also discuss the current research gaps and what could be improved to enable the operation of inland autonomous ships.