Velocity obstacle algorithms for collision prevention at sea

Huang, Yamin; Gelder, Pieter van; Wen, Yuanqiao

doi:10.1016/j.oceaneng.2018.01.001

Cited by 131 publications

(62 citation statements)

References 16 publications

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“…The velocity obstacle (VO) algorithm has been applied in many fields, such as vehicles, robots, and unmanned aerial vehicles, to avoid collisions (Mercado et al, 2015; Wang, 2015; Lee et al, 2017). Because the VO algorithm itself provides not only conflict detection results but also an optional speed set, this method has gradually been applied in the ship field in recent years (Huang et al, 2018; Song et al, 2018). In the velocity space, the collision risk can be converted into visible velocity contours.…”

Section: Description Of the Collision Avoidance Methodsmentioning

confidence: 99%

“…These methods may struggle to make accurate judgements if the trajectory of a ship is nonlinear, however, so it is necessary to adopt a more effective method to assess risk. Huang et al (2018) used the velocity obstacle algorithm to monitor the risk of ship collisions. Shi et al (2018) applied the velocity obstacle algorithm to solve a multi-agent collision avoidance problem.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Multi-Objective Algorithm for Preventing Multi-Ship Collisions at Sea

Wang

Guan

et al. 2020

J. Navigation

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Avoidance of collisions at sea is crucial to navigational safety. In this paper, we use a distributed algorithm to communicate the entire collision avoidance trajectory information for each ship. In each communication, we suggest a new improvement function considering safety and efficiency to identify the avoidance ship in each cycle. Considering the nonlinear collision avoidance trajectory of ships, a new method for calculating the degree of danger using a velocity obstacle algorithm is proposed. Therefore, in each communication, each ship considers the avoidance behaviours of other ships in planning its avoidance trajectory. Additionally, we combine bi-criterion evolution (BCE) and the ant lion optimiser to plan the entire collision avoidance path. Three scenarios are designed to demonstrate the performance of this method. The results show that the proposed method can find a suitable collision-free solution for all ships.

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Section: Description Of the Collision Avoidance Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Multi-Objective Algorithm for Preventing Multi-Ship Collisions at Sea

Wang

Guan

et al. 2020

J. Navigation

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“…Since then, a family of VO algorithm have been developed for preventing collisions, such as Ellipse-Based VO (EBVO) [16], Cooperative Collision Avoidance (CCA) [17]. VO algorithms have been applied in different scenarios, such as ship collision avoidance [18], safe maritime navigation for Unmanned Aerial Vehicle (UAV) [19]. multi-robot navigation [20].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Path Planning for Autonomous Driving on Branch Streets With Crossing Pedestrian Avoidance Guidance

Jia

Luo

et al. 2019

IEEE Access

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This paper presents a real-time dynamic path planning method for autonomous driving to avoid collision with crossing pedestrian on branch streets. The velocity obstacle algorithms are introduced to pick up the collision-free velocities for vehicles. In this method, the curvilinear lane edges are considered as static obstacle while crossing pedestrians and approaching vehicles are considered as velocity obstacles. The paths planning of vehicles are optimized by considering the delay minimum and comfort of drivers under the constraints of appropriate parameters for veer, throttle, or brake systems. A single vehicle's path planning and multi-vehicles 'coordinated or uncoordinated paths planning with crossing pedestrian collision avoidance are experimentally simulated including the longitudinal and lateral motions planning of vehicles. The simulation results demonstrate the effectiveness of the proposed method and indicate its wide practical application on autonomous driving to improve the traffic safety of branch streets. INDEX TERMS Autonomous vehicle, path planning, velocity obstacle, optimal control.

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“…With the maturity and perfection of artificial intelligent technology, through the people [12] workers swarm algorithm, genetic algorithm [13] , mimicry physics optimization algorithm [14] , simulated annealing algorithm [15] , the particle swarm algorithm [16] based on depth competition Q learning algorithm and A * algorithm [17] calculation of collision risk and loss of voyage, such as the objective function to achieve the optimal give way to the timing, safety, avoiding collision, and resume to resume time. At the same time, scholars also use the advantages of intelligent algorithms and models to combine the theory of ship collision avoidance field, ship dynamic boundary theory, ship motion mathematical model and domain model with various intelligent algorithms [18][19][20][21][22] to establish the optimization model of ship automatic collision avoidance. In the above studies, although relevant intelligent algorithms are used to put forward collision avoidance schemes, the change rules of collision circles and possible collision points in collision avoidance process have not been fully clarified, and the guiding significance of collision avoidance has not been fully explained.…”

Section: Introductionmentioning

confidence: 99%

Ship Collision Avoidance Decision Model and Simulation Based on Collision Circle

Zhang¹,

Hu²,

Liao³

2019

TransNav

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In order to give consideration to both comprehensive evaluation and efficient decision-making in collision avoidance decision-making process, a collision avoidance decision-making model based on collision circle is proposed by introducing the concept of collision circle. Firstly, the factors causing ship collision are analyzed. Secondly, the static and dynamic characteristics of collision circles are analyzed and summarized by using collision circle simulation cases. Thirdly, based on the static characteristics, a reasonably distributed collision avoidance decision model of (Possible Point of Collision,PPC) was established. Finally, the spatial data operations core algorithm (Java Topology Suite, JTS) is used for logical operation and visualization, so as to realize the ship collision avoidance evaluation and decision. The decision model was used to verify the accident scenario of ʺSANCHIʺ, and the results showed that the obtained collision avoidance scheme was reasonable and in line with the ʺInternational Regulations for Preventing Collisions at Seaʺ and safety requirements, thus providing a reference for maritime operators to avoid collisions between ships.

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Velocity obstacle algorithms for collision prevention at sea

Cited by 131 publications

References 16 publications

Distributed Multi-Objective Algorithm for Preventing Multi-Ship Collisions at Sea

Distributed Multi-Objective Algorithm for Preventing Multi-Ship Collisions at Sea

Dynamic Path Planning for Autonomous Driving on Branch Streets With Crossing Pedestrian Avoidance Guidance

Ship Collision Avoidance Decision Model and Simulation Based on Collision Circle

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