Authors:
Afef Awadid
1
;
André Meyer-Vitali
2
;
Dominik Vereno
3
and
Maxence Gagnant
1
Affiliations:
1
Technological Research Institute SystemX, Palaiseau, France
;
2
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany
;
3
Josef Ressel Centre for Dependable System-of-Systems Engineering, Salzburg, Austria
Keyword(s):
Intelligent Transportation Systems (ITS), ITS Architecture Design and Modeling, Large Language Model (LLM), Retrieval-Augmented Generation (RAG), Modeling Assistant, ITS Reference Architectures.
Abstract:
Intelligent Transportation Systems (ITS) have significantly transformed the transportation domain by addressing critical challenges such as traffic safety, cost, and energy efficiency. However, the increasing complexity of ITS—arising from the extensive range of applications and technologies they encompass—has made their architectural design modeling time-consuming and challenging, particularly for modelers lacking specialized expertise. Recent advancements in the literature suggest that large language model (LLM)-based modeling assistants offer a promising solution to mitigate these challenges. In this context, this paper introduces the RAG for Intelligent Transportation Systems Architecture (RITSA) project, which seeks to develop a retrieval-augmented generation (RAG) system to support ITS designers/ modelers throughout the architecture design process.