HPC Platform for Railway Safety-Critical Functionalities Based on Artificial Intelligence

Author:

Labayen Mikel12ORCID,Medina Laura3,Eizaguirre Fernando4ORCID,Flich José3ORCID,Aginako Naiara2ORCID

Affiliation:

1. Autonomous Vehicle Department, CAF Signalling, 20018 Donostia, Spain

2. Computer Sciences and Artificial Intelligence Department, University of the Basque Country, 20018 Donostia, Spain

3. Computer Engineering Department, Universitat Politècnica de València, 46022 Valencia, Spain

4. Embedded Systems Department, Ikerlan Technology Research Centre, 20500 Arrasate/Mondragón, Spain

Abstract

The automation of railroad operations is a rapidly growing industry. In 2023, a new European standard for the automated Grade of Automation (GoA) 2 over European Train Control System (ETCS) driving is anticipated. Meanwhile, railway stakeholders are already planning their research initiatives for driverless and unattended autonomous driving systems. As a result, the industry is particularly active in research regarding perception technologies based on Computer Vision (CV) and Artificial Intelligence (AI), with outstanding results at the application level. However, executing high-performance and safety-critical applications on embedded systems and in real-time is a challenge. There are not many commercially available solutions, since High-Performance Computing (HPC) platforms are typically seen as being beyond the business of safety-critical systems. This work proposes a novel safety-critical and high-performance computing platform for CV- and AI-enhanced technology execution used for automatic accurate stopping and safe passenger transfer railway functionalities. The resulting computing platform is compatible with the majority of widely-used AI inference methodologies, AI model architectures, and AI model formats thanks to its design, which enables process separation, redundant execution, and HW acceleration in a transparent manner. The proposed technology increases the portability of railway applications into embedded systems, isolates crucial operations, and effectively and securely maintains system resources.

Funder

RIA

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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