An intelligent method for real-time ship collision risk assessment and visualization

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Ship collision attracts prevalent attention due to its high occurrence frequency and severe potential conse-quence. It is therefore of pressing importance to prevent ship collision at sea for safe maritime transporta-tion. Non-linear Velocity Obstacle (NL-VO) algorithm has received increasing attention in maritime colli-sion avoidance by taking the dynamics of ship action during the encounter process into consideration. How-ever, one precondition of NL-VO algorithm is that the trajectory of target ship needs to be known in ad-vance, which makes the application of this algorithm limited in the historical ship collision risk analysis ra-ther than the in real-time collision avoidance. Although the generalized velocity obstacle algorithm over-comes this limitation using the trajectory prediction module, the trajectory uncertainty of the target ship is not discussed leading to the possible inaccurate collision risk assessment. Therefore, this paper presents a real-time collision risk assessment method based on an improved NL-VO algorithm by including the uncer-tainty analysis of the target ship’s predicted trajectory. The proposed method consists of two main modules: trajectory uncertainty module assumes that the increase in the radius of the circular restricted area is con-sistent with the Wiener process; collision risk assessment module utilizes the non-linear velocity obstacle algorithm combined with the dynamic circular restricted area to evaluate the potential collisions. Several encounter scenarios in a specific port channel are designed to demonstrate the feasibility of using this pro-posed method to assess ship collision risk in real-time. The result shows that this improved NL-VO algo-rithm can timely identify a ship that is in danger of colliding with the own ship and know when the collision will occur, which contributes to reducing ship collision occurrence probability.
Original languageEnglish
Title of host publicationDevelopments in the Collision and Grounding of Ships and Offshore Structures
EditorsCarlos Guedes Soares
Pages293-300
Number of pages8
ISBN (Electronic)9781003002420
Publication statusPublished - 2020
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Collision and Grounding of Ships and Offshore Structures - Lisbon, Portugal
Duration: 21 Oct 201923 Oct 2019
Conference number: 8

Publication series

NameProceedings in Marine Technology and Ocean Engineering
PublisherCRC Press Taylor & Francis Group, A BALKEMA BOOK
Volume4
ISSN (Print)2638-647X
ISSN (Electronic)2638-6461

Conference

ConferenceInternational Conference on Collision and Grounding of Ships and Offshore Structures
Abbreviated titleICCGS
CountryPortugal
CityLisbon
Period21/10/201923/10/2019

Keywords

  • collision risk
  • NL-VO algorithm
  • trajectory uncertainty

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  • Projects

    D4V

    Bergström, M., Du, L., Kujala, P., Basnet, S., Chaal, M. & Sormunen, O.

    01/12/201631/12/2019

    Project: Business Finland: Other research funding

    Cite this

    Du, L., Valdez Banda, O., & Kujala, P. (2020). An intelligent method for real-time ship collision risk assessment and visualization. In C. Guedes Soares (Ed.), Developments in the Collision and Grounding of Ships and Offshore Structures (pp. 293-300). (Proceedings in Marine Technology and Ocean Engineering; Vol. 4).