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

Abstract

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.

Publication DOI: https://doi.org/10.1111/exsy.70050
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
Aston University (General)
Funding Information: This work was funded by the UKRI EPSRC EP/Y028813/1 ‘National Edge AI Hub for Real Data: Edge Intelligence for Cyber-disturbances and Data Quality’.
Additional Information: Copyright © 2025 The Author(s). Expert Systems published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Uncontrolled Keywords: ADAS,automated driving system,knowledge-based system,performance evaluation,system architecture,Control and Systems Engineering,Theoretical Computer Science,Computational Theory and Mathematics,Artificial Intelligence
Publication ISSN: 1468-0394
Last Modified: 28 May 2025 07:39
Date Deposited: 06 May 2025 11:41
Full Text Link:
Related URLs: https://onlinel ... 1111/exsy.70050 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2025-06
Published Online Date: 2025-05-05
Accepted Date: 2025-04-12
Authors: Saez-Perez, Javier
Diez-Tomillo, Julio
Tena-Gago, David
Alcaraz Calero, Jose Maria (ORCID Profile 0000-0002-2654-7595)
Wang, Qi

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