Collision risk assessment for ships

Tam, CheeKuang; Bucknall, Rwg

doi:10.1007/s00773-010-0089-7

Cited by 109 publications

(75 citation statements)

References 11 publications

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“…It first reads in velocity (V i ) of the ith ship, where i is the index of the vessel. Based on V i , the algorithm starts to build the ship domain by adopting the shape proposed in Tam and Bucknall (2010). A ship domain alters its shape according to specific velocity; a more circular shape is constructed if vessel is travelling with low speed and half-elliptical shape is used for a high speed vessel.…”

Section: Dynamic Obstacles Representationmentioning

confidence: 99%

Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment

2015

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a b s t r a c tUnmanned surface vehicles (USVs) have been deployed over the past decade. Current USV platforms are generally of small size with low payload capacity and short endurance times. To improve effectiveness there is a trend to deploy multiple USVs as a formation fleet. This paper presents a novel computer based algorithm that solves the problem of USV formation path planning. The algorithm is based upon the fast marching (FM) method and has been specifically designed for operation in dynamic environments using the novel constrained FM method. The constrained FM method is able to model the dynamic behaviour of moving ships with efficient computation time. The algorithm has been evaluated using a range of tests applied to a simulated area and has been proved to work effectively in a complex navigation environment.

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Section: Dynamic Obstacles Representationmentioning

confidence: 99%

Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment

2015

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“…The state machine does not discriminate on whether the ownship is overtaking another vessel or is being overtaken, but this can be done by looking at which vessel has the higher speed (Tam and Bucknall, 2010). HO Head-on state.…”

Section: State Machinementioning

confidence: 99%

Hybrid Collision Avoidance for ASVs Compliant With COLREGs Rules 8 and 13–17

et al. 2020

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This paper presents a three-layered hybrid collision avoidance (COLAV) system for autonomous surface vehicles, compliant with rules 8 and 13-17 of the International Regulations for Preventing Collisions at Sea (COLREGs). The COLAV system consists of a high-level planner producing an energy-optimized trajectory, a model predictive control based mid-level COLAV algorithm considering moving obstacles and the COLREGs, and the branching-course model predictive control algorithm for short-term COLAV handling emergency situations in accordance with the COLREGs. Previously developed algorithms by the authors are used for the high-level planner and short-term COLAV, while we in this paper further develop the mid-level algorithm to make it comply with COLREGs rules 13-17. This includes developing a state machine for classifying obstacle vessels using a combination of the geometrical situation, the distance and time to the closest point of approach (CPA) and a new CPA-like measure. The performance of the hybrid COLAV system is tested through numerical simulations for three scenarios representing a range of different challenges, including multi-obstacle situations with multiple simultaneously active COLREGs rules, and also obstacles ignoring the COLREGs. The COLAV system avoids collision in all the scenarios, and follows the energy-optimized trajectory when the obstacles do not interfere with it. Keywords: Hybrid collision avoidance, Autonomous surface vehicle (ASV), COLREGs, COLREGs compliant, Model predictive control (MPC), Energy-optimized control arXiv:1907.00198v2 [eess.SY] 14 Jul 20192018, Falco navigated autonomously between two ports in Finland 2 . Reports state that in excess of 75 % of maritime accidents are due to human errors (Chauvin, 2011;Levander, 2017), indicating that there is also a potential for increased safety in addition to the economical and environmental benefits.An obvious prerequisite for autonomous ship operations is the development of robust and wellfunctioning collision avoidance (COLAV) systems. In addition to generating collision-free maneuvers, a COLAV system must adhere to the "rules of the road" of the oceans, i.e. the International Regulations for Preventing Collisions at Sea (COLREGs) (Cockcroft and Lameijer, 2004). These rules are written for human ship operators and include qualitative requirements on how to perform safe and readily observable maneuvers. Part B of the COLREGs concern steering and sailing, and includes the following rules that are the most relevant to a motion control system: Rule 8Requires maneuvers to be readily observable and to be done in ample time. Rules 13-15 Describe the maneuvers to perform in cases of overtaking, head-on and crossing situations. Participants in crossing situations are defined by the terms give-way and stand-on vessels. Rule 16Requires that a give-way vessel must take early and substantial action to keep clear of the stand-on vessel. Rule 17Consists of two main parts. The first part requires a stand-on vessel to maintain its course and speed, whi...

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“…Hence, it is reasonable to build the ship domain according to the speed of the target vessel. Referring to ship domain of Tam [40], the domain model of the target vessel can be established in Figure 13a, and also changed by the two parameters Rbow and Rstern. They are given by…”

Section: Target Vessel Dynamic Domain Modelmentioning

confidence: 99%

An Automatic Navigation System for Unmanned Surface Vehicles in Realistic Sea Environments

et al. 2018

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Abstract:In recent years, unmanned surface vehicles (USVs) have received notable attention because of their many advantages in civilian and military applications. To improve the autonomy of USVs, this paper describes a complete automatic navigation system (ANS) with a path planning subsystem (PPS) and collision avoidance subsystem (CAS). The PPS based on the dynamic domain tunable fast marching square (DTFMS) method is able to build an environment model from a real electronic chart, where both static and dynamic obstacles are well represented. By adjusting the Saturation, the generated path can be changed according to the requirements for security and path length. Then it is used as a guidance trajectory for the CAS through a dynamic target point. In the CAS, according to finite control set model predictive control (FCS-MPC) theory, a collision avoidance control algorithm is developed to track trajectory and avoid collision based on a three-degree of freedom (DOF) planar motion model of USV. Its target point and security evaluation come from the planned path and environmental model of the PPS. Moreover, the prediction trajectory of the CAS can guide changes in the dynamic domain model of the vessel itself. Finally, the system has been tested and validated using the situations of three types of encounters in a realistic sea environment.

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Collision risk assessment for ships

Cited by 109 publications

References 11 publications

Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment

Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment

Hybrid Collision Avoidance for ASVs Compliant With COLREGs Rules 8 and 13–17

An Automatic Navigation System for Unmanned Surface Vehicles in Realistic Sea Environments

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