Incorporating Large Language Models (LLMs) into Transportation Safety Analytics
-
2024-12-01
-
Details
-
Creators:
-
Corporate Creators:
-
Corporate Contributors:
-
Subject/TRT Terms:
-
Publication/ Report Number:
-
Resource Type:
-
Geographical Coverage:
-
Edition:Final Report
-
Corporate Publisher:
-
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.
-
Format:
-
Funding:
-
Collection(s):
-
Main Document Checksum:urn:sha-512:2c70614d159b34fd9c7c63da822cd283c01468840f1bcc55e03132f14344a3f8ac5de4958ca0da11c3f5cb6852e535b35b13f041d3c32821212d26d4f6e70232
-
Download URL:
-
File Type: