Publication
RITSA: Toward a Retrieval-Augmented Generation System for Intelligent Transportation Systems Architecture
Afef Awadid; André Meyer-Vitali; Dominik Vereno; Maxence Gagnant
In: Proceedings of the 13th International Conference on Model-Based Software and Systems Engineering - MBSE-AI Integration. International Conference on Model-Driven Engineering and Software Development (MODELSWARD-2025), MBSE-AI Integration, February 26-28, Porto, Portugal, Pages 466-473, ISBN 978-989-758-729-0, SciTePress, 2/2025.
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.