Evolutionary sets of safe ship trajectories with speed reduction manoeuvres within traffic separation schemes

Szlapczynski, Rafal

doi:10.2478/pomr-2014-0004

Cited by 10 publications

(7 citation statements)

References 11 publications

(12 reference statements)

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“…u 1 = α r -reference rudder angle of the own ship, u 2 = n r -reference rotational speed of the own ship's screw propeller, u 3 = H r -reference pitch of the adjustable propeller of the own ship, u j1 = ψ j -course of the j-th ship, u j2 = V j -speed of the j-th ship [5,7,19].…”

Section: Fig 1 Situation Of Relative Motion Of Own Ship (Green Trajmentioning

confidence: 99%

The Sensitivity of State Differential Game Vessel Traffic Model

Lisowski

2016

Polish Maritime Research

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Section: Fig 1 Situation Of Relative Motion Of Own Ship (Green Trajmentioning

confidence: 99%

The Sensitivity of State Differential Game Vessel Traffic Model

Lisowski

2016

Polish Maritime Research

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“…On topic of ship's trajectory planning, a number of studies have been performed and reviewed [18,26]. For example, the existing approaches cover the Sequential Gradient Restoration Algorithm [14], Recursive Algorithm [5], Fuzzy Set Theory [6][7], Knowledge-based System [11], the Interval Programming [2], the Maze Routing Algorithm [21], the Fast Marching Method [13], Cooperative Path Planning Algorithm [29], Distributed Decision Support Formulation [35], the Artificial Potential Field [34], the Fuzzy Logic based method [15][16], Genetic Algorithm [8,31,32], Evolutionary Algorithm [17,22,23,24,25,28], the Ant Colony Algorithm [10,30], the Danger Immune Algorithm [33]. Based on the methods, the approaches assume that ship's trajectory planning can be categorized into two general groups, namely the deterministic and heuristic ones [26].…”

Section: Introductionmentioning

confidence: 99%

Modelling of Ship’s Trajectory Planning in Collision Situations by Hybrid Genetic Algorithm

Liu

Cai

et al. 2018

Polish Maritime Research

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Ship collision-avoidance trajectory planning aims at searching for a theoretical safe-critical trajectory in accordance with COLREGs and good seamanship. In this paper, a novel optimal trajectory planning based on hybrid genetic algorithm is presented for ship collision avoidance in the open sea. The proposed formulation is established based on the theory of the Multiple Genetic Algorithm (MPGA) and Nonlinear Programming, which not only overcomes the inherent deficiency of the Genetic Algorithm (GA) for premature convergence, but also guarantees the practicality and consistency of the optimal trajectory. Meanwhile, the encounter type as well as the obligation of collision avoidance is determined according to COLREGs, which is then considered as the restricted condition for the operation of population initialization. Finally, this trajectory planning model is evaluated with a set of test cases simulating various traffic scenarios to demonstrate the feasibility and superiority of the optimal trajectory.

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“…The optimal control theory considering physical constraints was put forward to solve the problems of ship path planning (Djouani & Hamam 1995). Researches based on optimal theory have designed the ship path controller using methods like linear quadratic regulator (LQR) (Thomas & Sclavounos 2006, Mucha & el Moctar 2013 and evolutionary algorithms (Szłapczyński 2013). The model predictive control (MPC) approach, which allows multiple control inputs to response to the ship motion in the under-actuated system, has been used for path following (Oh & Sun 2009, Li et al 2010, and improved with disturbance compensating unit to apply to ship heading control (Li & Sun 2012).…”

Section: Introductionmentioning

confidence: 99%

Ship Course Following and Course Keeping in Restricted Waters Based on Model Predictive Control

Liu¹,

Ma²,

Gu³

2018

TransNav

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Ship navigation safety in restricted water areas is of great concern to crew members, because ships sailing in close proximity to banks are significantly affected by the so-called ship-bank interaction. The purpose of this paper is to apply the optimal control theory to help helmsmen adjust ships' course and maintain the target course in restricted waters. To achieve this objective, the motion of a very large crude carrier (VLCC) close to a bank is modeled with the linear equations of manoeuvring and the influence of bank effect on the ship hydrodynamic force is considered in the model. State-space framework is cast in a Multiple-Input Multiple-Output (MIMO) system, where the offset-free model predictive control (MPC) is designed for course following and the linear quadratic regulator (LQR) is used for course keeping. Simulation results show that the control methods effectively work in ship course following and course keeping with varying ship-bank distances and water depths. The advantage of adopting speed variation as the second control input is obvious.

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Evolutionary sets of safe ship trajectories with speed reduction manoeuvres within traffic separation schemes

Abstract: In the previous paper the author presented

Cited by 10 publications

References 11 publications

The Sensitivity of State Differential Game Vessel Traffic Model

The Sensitivity of State Differential Game Vessel Traffic Model

Modelling of Ship’s Trajectory Planning in Collision Situations by Hybrid Genetic Algorithm

Ship Course Following and Course Keeping in Restricted Waters Based on Model Predictive Control

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