TY - GEN
T1 - Fault injection method for safety and controllability evaluation of automated driving
AU - Uriagereka, Garazi Juez
AU - Lattarulo, Ray
AU - Rastelli, Joshue Perez
AU - Calonge, Estibaliz Amparan
AU - Ruiz Lopez, Alejandra
AU - Espinoza Ortiz, Huascar
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/31
Y1 - 2017/7/31
N2 - Advanced Driver Assistance Systems (ADAS) and automated vehicle applications based on embedded sensors have become a reality today. As road vehicles increase its autonomy and the driver shares his role in the control loop, novel challenges on their dependability assessment arise. One key issue is that the notion of controllability becomes more complex when validating the robustness of the automated vehicle in the presence of faults. This paper presents a simulation-based fault injection approach aimed at finding acceptable controllability properties for the model-based design of control systems. We focus on determining the best fault models inserting exceptional conditions to accelerate the identification of specific areas for testing. In our work we performed fault injection method to find the most appropriate safety concepts, controllability properties and fault handling strategies at early design phases of lateral control functions based on the error in the Differential GPS signal.
AB - Advanced Driver Assistance Systems (ADAS) and automated vehicle applications based on embedded sensors have become a reality today. As road vehicles increase its autonomy and the driver shares his role in the control loop, novel challenges on their dependability assessment arise. One key issue is that the notion of controllability becomes more complex when validating the robustness of the automated vehicle in the presence of faults. This paper presents a simulation-based fault injection approach aimed at finding acceptable controllability properties for the model-based design of control systems. We focus on determining the best fault models inserting exceptional conditions to accelerate the identification of specific areas for testing. In our work we performed fault injection method to find the most appropriate safety concepts, controllability properties and fault handling strategies at early design phases of lateral control functions based on the error in the Differential GPS signal.
KW - Automated driving
KW - Advanced Driver Assistance Systems
KW - ADAS
KW - Automated vehicle applications
KW - Embedded sensors
KW - Simulation-based fault
KW - Fault injection method
KW - Differential GPS signal
KW - Safety concepts
KW - Automated driving
KW - Advanced Driver Assistance Systems
KW - ADAS
KW - Automated vehicle applications
KW - Embedded sensors
KW - Simulation-based fault
KW - Fault injection method
KW - Differential GPS signal
KW - Safety concepts
UR - http://www.scopus.com/inward/record.url?scp=85028050643&partnerID=8YFLogxK
U2 - 10.1109/ivs.2017.7995977
DO - 10.1109/ivs.2017.7995977
M3 - Conference contribution
SN - 978-1-5090-4805-2
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 1867
EP - 1872
BT - unknown
PB - IEEE
T2 - 28th IEEE Intelligent Vehicles Symposium, IV 2017
Y2 - 11 June 2017 through 14 June 2017
ER -