SafeMTS Report: Applying Large Language Models to Maritime Near-Miss Safety Data Analysis

doi:10.21949/rdm1-cf20

i

SafeMTS Report: Applying Large Language Models to Maritime Near-Miss Safety Data Analysis

2025-12-01
By United States. Department of Transportation. Bureau of Transportation Statistics

File Language:

English

Details

Corporate Creators:

United States. Department of Transportation. Bureau of Transportation Statistics
Contributors:

Bohlman, Michael ; Dai, Honglei ; Doucette, Curtis ; Fischman, Allison ; Inozu, Bahadir ; Irwin, Benjamin ; Lemons, Amanda ; Nabach, Will ; Schaedel, Peter ; Sumner, Brian
Subject/TRT Terms:

Data Analysis Datasets Incident Detection Large Language Models Maritime Industry Maritime Safety Near Crashes Predictive Models Ship Pilots Water Transportation Crashes
DOI:

https://doi.org/10.21949/rdm1-cf20
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

United States. Department of Transportation. Bureau of Transportation Statistics
Abstract:

This report describes the methods, models and results of the application of large language models to maritime near-miss safety data to increase analytical efficiency and accuracy among diverse industry data within the SafeMTS (Safe Maritime Transportation System) program.
Format:

PDF
Collection(s):

BTS Products
Main Document Checksum:

urn:sha-512:cd3784b3cd88005bc138ea395bea10e0bb7291f6f4185463c36694188601dc99dda9c3ad5385ea400e20bcab68ec01f29472817817cc6ad427a2dee3cd52e98c
Download URL:

https://rosap.ntl.bts.gov/view/dot/89587/dot_89587_DS1.pdf
File Type:

[PDF - 1.96 MB ]

File Language:

English

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