TY - GEN
T1 - Programmable Systems for Intelligence in Automobiles (PRYSTINE)
T2 - Technical Progress after Year 2
AU - Druml, Norbert
AU - Debaillie, Bjom
AU - Anghel, Andrei
AU - Ristea, Nicolae Catalin
AU - Fuchs, Jonas
AU - Dubey, Anand
AU - Reisland, Torsten
AU - Hartstem, Maike
AU - Rack, Viktor
AU - Ryabokon, Anna
AU - Ozols, Kaspars
AU - Novickis, Rihards
AU - Levinskis, Aleksandrs
AU - Veledar, Omar
AU - MacHer, Georg
AU - Jany-Luig, Johannes
AU - Solmaz, Selim
AU - Reckenzaun, Jakob
AU - Mohan, Naveen
AU - Ophir, Shai
AU - Stettinger, Georg
AU - Diaz, Sergio
AU - Marcano, Mauricio
AU - Villagra, Jorge
AU - Castellano, Andrea
AU - Beekelaar, Rutger
AU - Tango, Fabio
AU - Vanne, Jarno
AU - Holma, Kalle
AU - Icoglu, Oguz
AU - Dimitrakopoulos, George
PY - 2020/8
Y1 - 2020/8
N2 - Autonomous driving has the potential to disruptively change the automotive industry as we know it today. For this, fail-operational behavior is essential in the sense, plan, and act stages of the automation chain in order to handle safety-critical situations by its own, which currently is not reached with state-of-The-Art approaches.The European ECSEL research project PRYSTINE realizes Fail-operational Urban Surround perceptION (FUSION) based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments. This paper showcases some of the key results (e.g., novel Radar sensors, innovative embedded control and E/E architectures, pioneering sensor fusion approaches, AI controlled vehicle demonstrators) achieved until year 2.
AB - Autonomous driving has the potential to disruptively change the automotive industry as we know it today. For this, fail-operational behavior is essential in the sense, plan, and act stages of the automation chain in order to handle safety-critical situations by its own, which currently is not reached with state-of-The-Art approaches.The European ECSEL research project PRYSTINE realizes Fail-operational Urban Surround perceptION (FUSION) based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments. This paper showcases some of the key results (e.g., novel Radar sensors, innovative embedded control and E/E architectures, pioneering sensor fusion approaches, AI controlled vehicle demonstrators) achieved until year 2.
KW - fail-operational
KW - FUSION
KW - perception
UR - http://www.scopus.com/inward/record.url?scp=85096357129&partnerID=8YFLogxK
U2 - 10.1109/DSD51259.2020.00065
DO - 10.1109/DSD51259.2020.00065
M3 - Conference contribution
AN - SCOPUS:85096357129
T3 - Proceedings - Euromicro Conference on Digital System Design, DSD 2020
SP - 360
EP - 369
BT - Proceedings - Euromicro Conference on Digital System Design, DSD 2020
A2 - Trost, Andrej
A2 - Zemva, Andrej
A2 - Skavhaug, Amund
PB - Institute of Electrical and Electronics Engineers
ER -