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Article Dans Une Revue IEEE Transactions on Nuclear Science Année : 2024

Assessment of Radiation-Induced Soft Error on Unmanned Surface Vehicles

Résumé

The presence of Unmanned Surface Vehicles (USVs) is increasingly frequent on lakes and water reservoirs, performing tasks such as monitoring water quality or delivering goods across the water. However, the emergence of such autonomous vessels raises concerns in terms of safety for people sharing the same environment and the risk of collisions with fixed structures and floating bodies, including other vessels. Therefore, the detection of obstacles and its reliable operation become primary in USVs. This work explores the effects caused by neutron radiation on an object detection algorithm tailored for USVs. Results report 77 silent data corruption (SDC)-induced failures, showing that radiation-induced soft errors contribute to missed and false detection of respectively existing and non-existent objects. Furthermore, results suggest that object detection algorithms running with the multi-core strategy ( FITSDC rate of 34.3 at sea level and 308.6 at Lake Titicaca) exhibit a 16.4% greater resilience to SDCs compared to the single-core strategy.
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Dates et versions

hal-04501997 , version 1 (13-03-2024)

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Paternité - Pas d'utilisation commerciale

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Citer

Marcos Antônio Junior Fleck, Elisa Pereira, Jonas Gava, Fernando Gehm Moraes, Ney Calazans, et al.. Assessment of Radiation-Induced Soft Error on Unmanned Surface Vehicles. IEEE Transactions on Nuclear Science, 2024, ⟨10.1109/TNS.2024.3378807⟩. ⟨hal-04501997⟩

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