Triton 2025 - Magazine - Page 40
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PERSPECTIVES
Navigating Safely
How Big Data can
Revolutionise Allision
Prevention in Maritime
Infrastructure
The Swedish Club talks to Axel Hörteborn, an engineer
at RISE, the Swedish Research Institute, who has a
background in civil and structural projects
and has been collaborating with the Club
When Axel 昀椀rst started working on maritime projects
in 2014, he was primarily interested in the feasibility
of building bridges over the deep, dramatic fjords of
Norway. The challenging conditions - deep waters and
unpredictable ship routes - prompted a critical question:
How likely is it that a vessel will collide with a bridge?
This question was sparked well before the DALI container ship
collided with the Francis Scott Key Bridge in Baltimore causing
six fatalities in 2024 and a more recent incident involving the
Brooklyn Bridge and a Mexican navy ship. Axel is now studying
the subject for a PhD funded by Sweden and Norway, focusing
not only on innovative bridge design but also on how AI could
be used to evaluate and mitigate the risks.
the risks associated
with ship movement
near critical maritime
structures.
Allision incidents are increasing
At the core of Axel’s research is the use of big data
modelling to analyse the probability of ship allisions with
infrastructure. Employing Automatic Identi昀椀cation System
data (AIS) - signals broadcast by virtually every commercial
vessel worldwide - he tracks vessel behaviour with
remarkable detail.
In the complex world of maritime navigation, one of the
most critical and challenging safety concerns is allision when a moving ship collides with a stationary object such
as a bridge. With the rise in global shipping traf昀椀c and
the construction of increasingly ambitious infrastructure
projects, understanding and preventing allisions is more
important than ever. Enter arti昀椀cial intelligence (AI): a tool
with the potential to transform how we assess and manage
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Triton 2025
2025
The Case for big data in
Allision Probability Modelling
Ships sometimes do things they shouldn’t: drifting
unexpectedly, making erratic turns, or failing to respond to
navigational cues. These anomalies are analysed by looking
