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

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.The novel approach presented in this work is being developed as a specific railway use case for autonomous train operation into SELENE European research project. This project has received funding from RIA—Research and Innovation action under grant agreement No. 871467

The ECSEL FRACTAL Project: A Cognitive Fractal and Secure edge based on a unique Open-Safe-Reliable-Low Power Hardware Platform

The objective of the FRACTAL project is to create a new approach to reliable edge computing. The computing node will be the building block of scalable Internet of Things (from Low Computing to High Computing Edge Nodes). The cognitive skill will be given by an internal and external architecture that allows forecasting its internal performance and the state of the surrounding world. The node will have the capability of learning how to improve its performance against the uncertainty of the environment. New industrial functions will flourish through the created space of the cognitive system. Cognitive advantages are brought to a resilient edge and a computing paradigm that lay down between the physical world and the cloud. © 2020 IEEE