二级自动驾驶车辆参考架构的设计、实现与验证

IF 3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Expert Systems Pub Date : 2025-05-05 DOI:10.1111/exsy.70050
Javier Saez-Perez, Julio Diez-Tomillo, David Tena-Gago, Jose M. Alcaraz-Calero, Qi Wang
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引用次数: 0

摘要

自动驾驶汽车代表着一个迅速扩张的全球市场,引起了工业界和学术界的极大关注。然而,现有的解决方案往往缺乏透明度,特别是在架构设计的公开方面,导致了分散的开发方法。为了解决这些问题,本文介绍了一种针对2级自动驾驶系统(ADS)量身定制的新型模块化参考架构。所提出的架构确保了不同车辆平台的安全性、可扩展性和适应性。利用开源的2级ADS实现OpenPilot进行了全面验证,证明了该架构在实时约束下实现可靠控制任务的实际可行性。这项工作弥合了工业和学术贡献之间的差距,为ADS开发的未来进步提供了可操作的见解和坚实的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Design, Implementation and Validation of a Level 2 Automated Driving Vehicle Reference Architecture

Design, Implementation and Validation of a Level 2 Automated Driving Vehicle Reference Architecture

Automated vehicles represent a rapidly expanding global market, drawing significant attention from both industry and academia. However, existing solutions often lack transparency, particularly in the disclosure of architectural designs, resulting in fragmented development approaches. To address these gaps, this paper introduces a novel, modular reference architecture tailored for Level 2 Automated Driving Systems (ADS). The proposed architecture ensures safety, scalability, and adaptability across diverse vehicle platforms. A comprehensive validation is conducted using OpenPilot, an open-source Level 2 ADS implementation, demonstrating the architecture's practical feasibility in achieving reliable control tasks under real-time constraints. This work bridges the gap between industrial and academic contributions, offering actionable insights and a robust foundation for future advancements in ADS development.

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来源期刊
Expert Systems
Expert Systems 工程技术-计算机:理论方法
CiteScore
7.40
自引率
6.10%
发文量
266
审稿时长
24 months
期刊介绍: Expert Systems: The Journal of Knowledge Engineering publishes papers dealing with all aspects of knowledge engineering, including individual methods and techniques in knowledge acquisition and representation, and their application in the construction of systems – including expert systems – based thereon. Detailed scientific evaluation is an essential part of any paper. As well as traditional application areas, such as Software and Requirements Engineering, Human-Computer Interaction, and Artificial Intelligence, we are aiming at the new and growing markets for these technologies, such as Business, Economy, Market Research, and Medical and Health Care. The shift towards this new focus will be marked by a series of special issues covering hot and emergent topics.
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