Rodríguez-Arozamena M, Matute J, Pérez J, Ozbay B, Tezcan D, Begecarslan E, Mutlukaya I, Buquerin KG, Volkersdorfer T, Hof HJ (2026)
Publication Type: Book chapter / Article in edited volumes
Publication year: 2026
Publisher: Springer
Series: Lecture Notes in Mobility
Book Volume: Part F1025
Pages Range: 731-737
DOI: 10.1007/978-3-032-06763-0_104
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.
APA:
Rodríguez-Arozamena, M., Matute, J., Pérez, J., Ozbay, B., Tezcan, D., Begecarslan, E.,... Hof, H.J. (2026). A Fail-Safe Decision Architecture for CCAM Applications. In (pp. 731-737). Springer.
MLA:
Rodríguez-Arozamena, Mario, et al. "A Fail-Safe Decision Architecture for CCAM Applications." Springer, 2026. 731-737.
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