IDAS: 使用 RAG 的智能驾驶辅助系统

IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Luis-Bernardo Hernandez-Salinas;Juan Terven;E. A. Chavez-Urbiola;Diana-Margarita Córdova-Esparza;Julio-Alejandro Romero-González;Amadeo Arguelles;Ilse Cervantes
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引用次数: 0

摘要

在快速发展的汽车技术领域,人们越来越清楚地认识到,汽车需要更智能、互动性更强的系统。本文介绍的智能驾驶辅助系统(IDAS)是一种人工智能系统,它能让驾驶员使用语音指令访问汽车的各种功能。IDAS 的主要组成部分是一个大语言模型(LLM),通过检索增强生成(RAG),它可以有效地阅读和理解汽车手册,从而提供基于上下文的即时帮助。此外,该系统还集成了语音识别和语音合成功能,可以理解多种语言的指令,从而改善不同驾驶员群体的用户体验。我们的结果表明,使用 GPT-4o-mini 和 Mistral Nemo 的管道响应时间最短为一秒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IDAS: Intelligent Driving Assistance System Using RAG
In the fast-growing automotive technology sector, it has become increasingly clear that there is a need for cars with smarter and more interactive systems. This article presents the Intelligent Driving Assistance System (IDAS), an artificial intelligence system that enables the driver to use voice commands to access various features of a car. The primary component of IDAS is a Large Language Model (LLM), which, through retrieval augmented generation (RAG), can efficiently read and understand the car manual for immediate context-based aid. In addition, this system incorporates speech recognition and speech synthesis capabilities, it can understand commands given in multiple languages, improving user experiences among diverse driver communities. Our results show a minimum response time of one second for the pipeline using GPT-4o-mini and Mistral Nemo.
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来源期刊
CiteScore
9.60
自引率
0.00%
发文量
25
审稿时长
10 weeks
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