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Published April 16, 2024 | Version v1
Conference paper Restricted

A Fail-Safe Decision Architecture for CCAM Applications

Creators

  • 1. TECNALIA Research & Innovation, Basque Research and Technology Alliance, Derio, Spain
  • 2. University of the Basque Country (UPV/EHU), Bilbao, Spain
  • 3. FEV Türkiye, Istanbul, Türkiye
  • 4. Technische Hochschule Ingolstadt, CARISSMA Institute of Electric, Connected and Secure Mobility (C-ECOS), Ingolstadt, Germany
  • 5. Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
  • 6. Universität Passau, Germany

Description

In the context of Connected, Cooperative, and Automated Mobility (CCAM), precise ego-vehicle positioning and environmental status assessment are crucial. However, these tasks can be susceptible to sensor failures, misuse, and cyberattacks. Automation disengagements and system redundancy are common strategies to achieve Minimum Risk Conditions when failures occur. This paper presents a Fail-Safe decision architecture formulated within the framework of the SELFY project (https://selfy-project.eu/ ). The main aim is to reduce inaccuracies in GNSS-derived positioning through the incorporation of sensor fusion, AI-guided situational assessment, trajectory planning, and mode decision components. Additionally, the architecture has been designed to enable real-time updates and communication with external entities, including the Vehicle Security Operations Centre.

Notes

This project has received funding from the Horizon Europe programme under grant agreement No. 101069748.

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Additional details

Funding

European Commission
SELFY - SELF assessment, protection & healing tools for a trustworthY and resilient CCAM 101069748