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An improved time discretized non-linear velocity obstacle method for multi-ship encounter detection

Published on Jan 15, 2020in Ocean Engineering2.73
· DOI :10.1016/J.OCEANENG.2019.106718
Pengfei Chen3
Estimated H-index: 3
(TU Delft: Delft University of Technology),
Yamin Huang6
Estimated H-index: 6
(TU Delft: Delft University of Technology)
+ 2 AuthorsP.H.A.J.M. van Gelder22
Estimated H-index: 22
(TU Delft: Delft University of Technology)
Abstract
Abstract Ship collision is one of the major contributors of maritime accidents. Quantitative risk analysis of such accidents is an effective tool for maritime safety administrations to understand the current risk level and propose risk mitigation measures. In this paper, an improved Time Discretized Non-linear Velocity obstacle (TD-NLVO) algorithm is proposed to detect multiple ship encounter situations using historical AIS data. Boolean operation on the individual NLVO is integrated with TD-NLVO using the union of the velocity-obstacle sets to determine a dangerous encounter situation according to the pre-set criteria. Two case studies are implemented to illustrate the capability of the proposed algorithm. A comparison is conducted between the previous and the improved methods. The results indicate that the improved method can effectively identify a multiple ship encounter which satisfies the pre-set criteria. The improved method has the potential to provide more detailed information for stakeholders e.g. maritime safety administration, etc. to propose risk mitigation measures as well as to improve the accuracy of geometric probability analysis for ship collision risk.
  • References (35)
  • Citations (1)
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References35
Newest
#2Michael Baldauf (World Maritime University)H-Index: 9
In shipping, collision risk is a serious safety threat. Risk probability estimations used for policymaking are derived from traffic density statistics, largely ignoring the decision-making process ...
3 CitationsSource
: We propose an innovative time-varying collision risk (TCR) measurement for ship collision prevention in this article. The proposed measurement considers the level of danger of the approaching ships and the capability of a ship to prevent collisions. We define the TCR as the probability of the overlap of ships' positions in the future, given the uncertainty of maneuvers. Two sets are identified: (1) the velocity obstacle set as the maneuvers of the own ship that lead to collisions with target s...
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#1Yamin Huang (TU Delft: Delft University of Technology)H-Index: 6
#2Linying Chen (TU Delft: Delft University of Technology)H-Index: 5
Last. P.H.A.J.M. van Gelder (TU Delft: Delft University of Technology)H-Index: 22
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Abstract Collision prevention is critical for navigation safety at sea. At early ages, researchers aimed at developing navigational assistance systems for enhancing situational awareness of human operators as human is at the core of collision avoidance. Recently, autonomous vehicles have gained a remarkable amount of attention with a focus on solving collision problems by machines. This results in two groups of studies, both working on preventing collisions but with different focuses: one aims a...
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#1Pengfei Chen (TU Delft: Delft University of Technology)H-Index: 3
#2Junmin Mou (WUT: Wuhan University of Technology)H-Index: 3
Last. P.H.A.J.M. van Gelder (TU Delft: Delft University of Technology)H-Index: 22
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Abstract Maritime accidents, especially ship collisions, have always been a threat to the safety of maritime transport industry, the regional and global economy, and societies, due to its dire consequences. In this paper, a novel method to model causational factors, one of the critical elements of probabilistic risk modelling of ship collision accidents, is proposed. A credal probabilistic graphical network model based on imprecise probabilities was established based on accident investigation re...
2 CitationsSource
#1Pengfei Chen (TU Delft: Delft University of Technology)H-Index: 3
#2Yamin Huang (TU Delft: Delft University of Technology)H-Index: 6
Last. P.H.A.J.M. van Gelder (TU Delft: Delft University of Technology)H-Index: 22
view all 4 authors...
Abstract Maritime transportation system has made a significant contribution to the development of the world economy. However, with the growth of quantity, scale, and speed of ships, maritime accidents still pose incrementing risk to individuals and societies in terms of multiple aspects, especially collision accidents between ships. Great effort is needed to prevent the occurrence of such accidents and to improve navigational safety and traffic efficiency. In this paper, extensive literature on ...
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In this paper, we propose a novel dynamic fuzzy ship domain that considers factors associated with both one's own ship and other ships. This is in contrast to existing ship domain models that operate from the perspective of one's own ship, considering only the factors relevant to that ship. First, the domain was determined by considering the distance of the ships around one's own ship in different directions, which sufficiently accounts for factors associated with one's own ship and with the oth...
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#1Yamin Huang (TU Delft: Delft University of Technology)H-Index: 6
#2Linying Chen (TU Delft: Delft University of Technology)H-Index: 5
Last. P.H.A.J.M. van Gelder (TU Delft: Delft University of Technology)H-Index: 22
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Abstract Numerous methods have been developed for ship collision prevention over the past decades. However, most studies are based on strong assumptions, such as the need for a constant velocity of the target-ship, the limitation to two-ship scenarios, the simplification of ships' dynamics, etc. Generalized Velocity Obstacle (GVO) algorithm can bridge these gaps. This paper presents a GVO algorithm for ship collision avoidance and designs a collision avoidance system (GVO-CAS). The proposed syst...
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#1Zhixiang Fang (WHU: Wuhan University)H-Index: 20
#2Hongchu Yu (WHU: Wuhan University)H-Index: 4
Last. Guojun Peng (UT: University of Tennessee)H-Index: 2
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Vessel risk analysis is critical for safe ship navigation and maritime safety management. Near-miss collisions by ships comprise an significant risk, which may be complicated by factors, such as the ship conditions, waterway environment, and driving behavior of any ships encountered. Previous studies have rarely considered how to automatically and adaptively estimate the risk of near-miss collisions for different situations, particularly in port areas. In this paper, we propose an automatic iden...
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Urban waterways have great potential in cargo transport to relieve the congestion in the overloaded road networks. This paper explores the potential of applying cooperative multi-vessel systems (CMVSs) to improve the safety and efficiency of transport in urban waterway networks. A framework consisting of vessel train formation (VTF) and cooperative waterway intersection scheduling (CWIS) is proposed. Two types of controllers are introduced. Intersection controllers solve the CWIS problems and as...
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Evaluating ship encounters probability efficiently is significant for maritime transportation risk analysis as well as improving maritime traffic safety. In practice, ship encounters probability estimate by using traditional observation or field experiments is nearly impossible due to the expensive cost. In this paper, we propose a methodology framework for evaluating ship encounters probability based on an agent-based simulation paradigm. Individual ship's navigation behavior is modeled as an a...
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#1Lei Du (Aalto University)H-Index: 1
#2Floris Goerlandt (Dal: Dalhousie University)H-Index: 23
Last. Pentti Kujala (Aalto University)H-Index: 29
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Abstract The safe navigation of ships is of high societal concern. A promising approach for analysing waterway risks is using non-accident critical events as surrogate indicators of collision accidents. These are typically detected in data from the Automatic Identification System (AIS). Recognizing the significant interest in this approach, this article provides a review and analysis of methods based on the detection of non-accident critical events from AIS data, which aim to provide insight int...
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