DS3.1 Automotive Safety Demonstration

The SAFEXPLAIN Auto Use Case implements an autonomous navigation pipeline on top of the CARLA simulator, focusing on explainability and safety. The system integrates a Carla bridge for simulator interaction, a Perception node for lane and object detection, and a Controller for safe vehicle actuation. A Decision node performs rule-based fusion, braking logic, and collision warnings, while a Supervision node monitors perception quality and anomalies. The Overlay node generates real-time visualizations of detections, warnings, and system status, supporting debugging and explainability. The architecture is managed by the SafeXplain middleware (State, Lifecycle, and Health Managers), ensuring consistent initialization, monitoring, and fault detection. Together, these components enable robust autonomous driving scenarios with transparent safety monitoring. This work is part of the SAFEXPLAIN Community (zenodo.org/communities/safexplain).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-22
DOI
https://doi.org/10.5281/zenodo.17226888
Primary Topic
Education, Psychology, and Social Research
Type
article
Field-Weighted Citation Impact
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article

DS3.1 Automotive Safety Demonstration

Zenodo (CERN European Organization for Nuclear Research)
Education, Psychology, and Social Research
article

DS3.1 Automotive Safety Demonstration

article en

Abstract

The SAFEXPLAIN Auto Use Case implements an autonomous navigation pipeline on top of the CARLA simulator, focusing on explainability and safety. The system integrates a Carla bridge for simulator interaction, a Perception node for lane and object detection, and a Controller for safe vehicle actuation. A Decision node performs rule-based fusion, braking logic, and collision warnings, while a Supervision node monitors perception quality and anomalies. The Overlay node generates real-time visualizations of detections, warnings, and system status, supporting debugging and explainability. The architecture is managed by the SafeXplain middleware (State, Lifecycle, and Health Managers), ensuring consistent initialization, monitoring, and fault detection. Together, these components enable robust autonomous driving scenarios with transparent safety monitoring. This work is part of the SAFEXPLAIN Community (zenodo.org/communities/safexplain).

Zenodo (CERN European Organization for Nuclear Research)
United States Department of the Navy (US)
Openalex Percentile: Top 36%
Education, Psychology, and Social Research
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