Incorporating Large Language Models (LLMs) into Transportation Safety Analytics [supporting dataset]

Tang, Jinwei; Luo, Yuebo; Li, Tianxin; Wang, Kai; Ding, Caiwen

doi:10.7910/DVN/ZUVVZD

i

Incorporating Large Language Models (LLMs) into Transportation Safety Analytics [supporting dataset]

Dataset

2025-02-23
By Tang, Jinwei ; Luo, Yuebo ; Li, Tianxin ; ...

File Language:

English

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Creators:

Tang, Jinwei ; Luo, Yuebo ; Li, Tianxin ; Wang, Kai ; Ding, Caiwen
Corporate Creators:

New England Transportation Consortium ; University of Massachusetts at Amherst
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:

Algorithms Crash Data Data Analysis Data Files Equity (Justice) Language Transportation Safety
DOI:

https://doi.org/10.7910/DVN/ZUVVZD
Resource Type:

Dataset
Right Statement:

Open Access; http://creativecommons.org/publicdomain/zero/1.0
Geographical Coverage:

United States
Corporate Publisher:

New England Transportation Consortium
Abstract:

This project focuses on enhancing transportation safety through LLMs. Its goal is to improve crash data analysis by highlighting disparities in traffic safety, particularly for vulnerable road users. Leveraging the Connecticut Crash Data Repository, the project develops an LLM algorithm to automatically analyze crash patterns and generate visual reports. This innovative approach by our interdisciplinary team combines expertise in machine learning and transportation safety, ensuring a comprehensive approach to these challenges. The project's outcomes are expected to influence policy and planning decisions, fostering safer transportation systems.

The total size of the ZIP file is 11,169 KB
Content Notes:

This item is made available under the terms of the Creative Commons Attribution 1.0 Universal (CC0 1.0) license https://creativecommons.org/publicdomain/zero/1.0/. Use the following citation:Caiwen Ding, 2025, "Incorporating Large Language Models (LLMs) into Transportation Safety Analytics and Equity", https://doi.org/10.7910/DVN/ZUVVZD, Harvard Dataverse, V1, UNF:6:dT5TC4Y70zP1+luBlaegiw== [fileUNF]
Format:

ZIP
Funding:

69A3552348301
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:6756df2b44f9df7c5844219cf0c6be45685a7aa746ff16267d9e356c36edcabe413f1507e9b602f4fb14acf12c6298835ef8a49fad8459e4857c5bda8181d019
Download URL:

https://rosap.ntl.bts.gov/view/dot/86802/dot_86802_DS1.zip
File Type:

[ZIP - 10.91 MB ]

Incorporating Large Language Models (LLMs) into Transportation Safety Analytics

This project focuses on enhancing transportation safety through LLMs. Its goal is to improve crash data analysis by highlighting disparities in traffi ...

Tang, Jinwei

;

Luo, Yuebo

File Language:

English

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