Assessment of Radiation-Induced Soft Error on Unmanned Surface Vehicles

The presence of unmanned surface vehicles (USVs) is increasingly frequent in 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...

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Vydané v:IEEE transactions on nuclear science Ročník 71; číslo 8; s. 1589 - 1597
Hlavní autori: Fleck, Marcos A., Pereira, Elisa G., Gava, Jonas F., Silva, Henrique B., Moraes, Fernando G., Calazans, Ney L.V., Meneguzzi, Felipe, Bastos, Rodrigo P., Reis, Ricardo A. L., Ost, Luciano, Garibotti, Rafael
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.08.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Predmet:
Algorithms
Autonomous vehicles
Engineering Sciences
Feature extraction
Floating bodies
Inference algorithms
Lakes
Micro and nanotechnologies
Microelectronics
Neutron radiation
Neutrons
Object recognition
object recognition algorithm
Obstacle avoidance
Radiation
Radiation effects
Reliability
Safety
Soft errors
Strategy
Surface vehicles
uncrewed surface vessels
unmanned surface vehicles (USVs)
Unmanned vehicles
Vessels
Water monitoring
Water quality
YOLO
Neutron radiation
Uncrewed Surface Vessels
Unmanned Surface Vehicles USVs
USVs
Object Recognition Algorithm
ISSN:0018-9499, 1558-1578
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Shrnutí:The presence of unmanned surface vehicles (USVs) is increasingly frequent in 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 their reliable operation becomes 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 nonexistent objects. Furthermore, results suggest that object detection algorithms running with the multicore strategy (<inline-formula> <tex-math notation="LaTeX">\text {FIT}_{\text {SDC}} </tex-math></inline-formula> 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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-9499
1558-1578
DOI:10.1109/TNS.2024.3378807