Ship Behaviour and Ship Bridge Allision Analysis
Licentiatavhandling, 2021

The demand for maritime transport has increased with the growing demand for worldwide trade. This has led to a major increase in maritime traffic and ship sizes over the last decades, which raises the probability of accidents. The methods used in maritime risk assessments today are based on old hypotheses that do not include all data available today. The main objective of this thesis is to develop numerical models and methods for the analysis of what is considered as normal navigation behaviour at sea today and improve the analysis of probability for ship-bridge allisions.

The first part of the thesis describes what is considered as normal meeting distance at sea today. This information is later used while identifying failure events to ensure that the event behaviour was not caused by other ships. These few cases are excluded from the methodology since the communication and situational awareness in the situations are not known. However, while studying the probability of ship-bridge accidents, it is also important to understand how waterway restrictions may affect the probability of ship-ship collisions. Therefore, this thesis also includes a study of how the improved knowledge concerning meeting distance could be used in a near ship-ship collision identification model. One of the main findings considering normal meeting distance is that small and large ships meet each other at a similar distance at sea.

In the second part of the thesis, a methodology is proposed to estimate the probability of ship-bridge allision. The presented methodology uses Automatic Identification System (AIS) data and a ship manoeuvring simulator to simulate and analyse marine traffic with regards to risks for accidents, such as ship-bridge allisions. A failure event identification method is also presented, which is needed to determine the frequency, duration and behaviour for the accident scenarios. The three events that were modelled and simulated in the simulator were: drifting ship, sharp turning ship and missing turning point. The probability of the different failure events corresponded to previous statistics confirming the AIS-based methodology. This means the methods to obtain the probability and duration of the failure events could be utilised in other areas. The simulation methodology was confirmed with the probability of grounding in the Great Belt VTS area.

This thesis firstly contributes to a better understanding of the modelling of probability for ship-bridge allisions. This will support bridge-building engineers who need to take into account accidental loads from ship-bridge allision while designing bridges. Secondly, this thesis also contributes to a better representation of normal behaviour at sea, which is used both in fairway designs and in estimations of ship-ship collisions.

ship domain

ship simulations

AIS data

failure statistics

risk modelling

Opponent: Pentti Kujala, Alto University, Finland

Författare

Axel Hörteborn

SSPA Sweden AB

A revisit of the definition of the ship domain based on AIS analysis

Journal of Navigation,; Vol. 3(2019)p. 777-794

Artikel i vetenskaplig tidskrift

A comparison of two definitions of ship domain for analysing near ship–ship collisions

Proceedings of The 8th International Conference on Collision and Grounding of Ships (ICCGS8) - Developments in the Collision and Grounding of Ships and Offshore Structures,; Vol. 2019(2020)p. 308-316

Paper i proceeding

Hörteborn, A. & Ringsberg, J.W. (2020). A method for risk analysis of ship collisions with stationary infrastructure using AIS data and a ship manoeuvring simulator

Styrkeområden

Informations- och kommunikationsteknik

Transport

Drivkrafter

Hållbar utveckling

Ämneskategorier

Transportteknik och logistik

Övrig annan teknik

Infrastrukturteknik

Annan samhällsbyggnadsteknik

Thesis for the degree of Licentiate – Department of Mechanics and Maritime Sciences: 2021:02

Utgivare

Chalmers tekniska högskola

Online

Opponent: Pentti Kujala, Alto University, Finland

Mer information

Senast uppdaterat

2021-01-13