Communication Dans Un Congrès Année : 2025

RITSA: Toward a Retrieval-Augmented Generation System for Intelligent Transportation Systems Architecture

Résumé

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.

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Dates et versions

hal-04900918 , version 1 (01-04-2025)

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  • HAL Id : hal-04900918 , version 1

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Afef Awadid, André Meyer-Vitali, Dominik Vereno, Maxence Gagnant. RITSA: Toward a Retrieval-Augmented Generation System for Intelligent Transportation Systems Architecture. 2nd Workshop on Model-based System Engineering and Artificial Intelligence - MBSE-AI Integration. Modelsward'2025, Feb 2025, Porto, Portugal. ⟨hal-04900918⟩
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