Kayotee: A Fault Injection-based System to Assess the Safety and Reliability of Autonomous Vehicles to Faults and Errors. Jha, S., Tsai, T., Hari, S., Sullivan, M., Kalbarczyk, Z., Keckler, S. W, & Iyer, R. K 2018. bibtex @Article{jha18kayotee,
author = {Jha, Saurabh and Tsai, Timothy and Hari, Siva and Sullivan, Michael and Kalbarczyk, Zbigniew and Keckler, Stephen W and Iyer, Ravishankar K},
title = {Kayotee: A Fault Injection-based System to Assess the Safety and Reliability of Autonomous Vehicles to Faults and Errors},
year = {2018},
comment = {* systematic FI into HW and SW components of autonomous driving systems (e.g., cars) * technology stack by nvidia * in closed-loop environment * inject transient faults (i.e., software state is being modified) * to assess error masking * fault injection points on different levels * CPU/GPU: transient faults in functional units * software: modify program output * workload-generation (i.e., traffic scenarios) * compare with fault-free execution * \# there aren't too much details in the paper (~4 pages)},
file = {:jha18kayotee - Kayotee_ A Fault Injection-based System to Assess the Safety and Reliability of Autonomous Vehicles to Faults and Errors.pdf:PDF},
groups = {fault injection},
timestamp = {2019-02-18},
}
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