Scalable Fail-degraded Systems for Autonomous Vehicles - A Survey
Autonomous vehicles represents a ground-breaking transportation technology which has the potential to provide many benefits to the society. To fully utilize this technology, it is essential that the autonomous vehicle maintains safe behavior under different conditions and in case of failures. Fail-d...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/419394 |
| Acceso en línea: | http://hdl.handle.net/10261/419394 |
| Access Level: | acceso abierto |
| Palabra clave: | Autonomous vehicles safety fault tolerance adaptive systems uncertainty |
| Sumario: | Autonomous vehicles represents a ground-breaking transportation technology which has the potential to provide many benefits to the society. To fully utilize this technology, it is essential that the autonomous vehicle maintains safe behavior under different conditions and in case of failures. Fail-degraded strategies allow the vehicle to react safely to these situations, while maintaining to some extent the vehicle’s autonomous functionality. However, defining a framework for scalable fail-degraded systems, given the system’s complexity, remains to be a challenge. This paper focuses on identifying concepts and tools that enables scalable fail-degraded behavior for autonomous vehicles. The article includes a taxonomy to clarify holistic monitoring and representation concepts. Based on these concepts, scalable monitoring techniques are identified and classified. Afterwards,safety reasoning frameworks and adaptation mechanisms for fail-degraded autonomous vehicles are discussed. According to the discussed literature, several research gaps are identified. |
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