Path planning and collision avoidance for autonomous surface vehicles I: a review

Autonomous surface vehicles are gaining increasing attention worldwide due to the potential benefits of improving safety and efficiency. This has raised the interest in developing methods for path planning that can reduce the risk of collisions, groundings, and stranding accidents at sea, as well as costs and time expenditure. In this paper, we review guidance, and more specifically, path planning algorithms of autonomous surface vehicles and their classification. In particular, we highlight vessel autonomy, regulatory framework, guidance, navigation and control components, advances in the industry, and previous reviews in the field. In addition, we analyse the terminology used in the literature and attempt to clarify ambiguities in commonly used terms related to path planning. Finally, we summarise and discuss our findings and highlight the potential need for new regulations for autonomous surface vehicles

Qualitative Process Analysis : Theoretical Requirements and Practical Implementation in Naval Domain

Understanding complex behaviours is an essential component of everyday life, integrated into daily routines as well as specialised research. To handle the increasing amount of data available from (logistic) dynamic scenarios, analysis of the behaviour of agents in a given environment is becoming more automated and thus requires reliable new analytical methods. This thesis seeks to improve analysis of observed data in dynamic scenarios by developing a new model for transforming sparse behavioural observations into realistic explanations of agent behaviours, with the goal of testing that model in a real-world maritime navigation scenario

Early detection of vessel collision situations in a vessel traffic services area

This study presents enhanced collision detection model in a Vessel Traffic Services (VTS) area. The proposed detection method of collision situations is based on the assumption that VTS station is provided with passage plans of all the vessels in a monitored area. By using an early detection model for prediction of possible collision situations, VTS stations could switch from the area-monitoring concept to the passage-monitoring system. An early detection model of collision risks in a VTS area uses vessels’ dynamic characteristics as inputs (vessels’ position, course over ground and speed), and delivers prediction of their future positions as output. In order to achieve the desired accuracy, the model takes into the account the intended course alterations and the impending environmental loads. The model is able to provide the outputs as early as the passage plans are submitted to a VTS monitored area. Hence, when discussing model’s capability for early detection of collision situations, improved VTS operating standards could be developed in order to achieve safer passages through enhanced collision avoidance strategies. Simulation results clearly show the advantages of the proposed model as a decision support tool for a VTS operator when combining passage plans with the analysis of environmental loads. First published online 18 November 201

Multiobjective Optimization Based Vessel Collision Avoidance Strategy Optimization

The vessel collision accidents cause a great loss of lives and property. In order to reduce the human fault and greatly improve the safety of marine traffic, collision avoidance strategy optimization is proposed to achieve this. In the paper, a multiobjective optimization algorithm NSGA-II is adopted to search for the optimal collision avoidance strategy considering the safety as well as economy elements of collision avoidance. Ship domain and Arena are used to evaluate the collision risk in the simulation. Based on the optimization, an optimal rudder angle is recommended to navigator for collision avoidance. In the simulation example, a crossing encounter situation is simulated, and the NSGA-II searches for the optimal collision avoidance operation under the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS). The simulation studies exhibit the validity of the method

AN EMPIRICAL MODEL OF SHIP DOMAIN FOR NAVIGATION IN RESTRICTED WATERS

Ph.DDOCTOR OF PHILOSOPH

MULTI-VESSELS COLLISION AVOIDANCE STRATEGY FOR AUTONOMOUS SURFACE VEHICLES BASED ON GENETIC ALGORITHM IN CONGESTED PORT ENVIRONMENT

An improved genetic collision avoidance algorithm is proposed in this study to address the problem that Autonomous Surface Vehicles (ASV) need to comply with the collision avoidance rules at sea in congested sea areas. Firstly, a collision risk index model for ASV safe encounters is established taking into account the international rules for collision avoidance. The ASV collision risk index and the distance of safe encounters are taken as boundary values of the correlation membership function of the collision risk index model to calculate the optimal heading of ASV in real-time. Secondly, the genetic coding, fitness function, and basic parameters of the genetic algorithm are designed to construct the collision avoidance decision system. Finally, the simulation of collision avoidance between ASV and several obstacle vessels is performed, including the simulation of three collision avoidance states head-on situation, crossing situation, and overtaking situation. The results show that the proposed intelligent genetic algorithm considering the rules of collision avoidance at sea can effectively avoid multiple other vessels in different situations