TY - JOUR
T1 - AutoRally
T2 - An Open Platform for Aggressive Autonomous Driving
AU - Goldfain, Brian
AU - Drews, Paul
AU - You, Changxi
AU - Barulic, Matthew
AU - Velev, Orlin
AU - Tsiotras, Panagiotis
AU - Rehg, James M.
N1 - Funding Information:
The authors wish to thank all of the undergraduate students who have helped build and maintain the fleet of AutoRally platforms, including Jason Gibson, Jeffrey McKendree, Alex-andra Miner, Dominic Pattison, Sarah Selim, Cory Wacht, and Justin Zheng. This work was made possible, in part, by the U.S. Army Research Office through the Multidisciplinary University Research Initiative award W911NF-11-1-0046 and Defense University Research Instrumentation Program awards W911NF-12-1-0377 and N00014-17-1-2318.
Publisher Copyright:
© 1991-2012 IEEE.
PY - 2019/2
Y1 - 2019/2
N2 - The technical challenge of creating a self-driving vehicle remains an open problem despite significant advancements from universities, car manufacturers, and technology companies. Full autonomy, known as level 5 (see Society of Automotive Engineers Levels of Driving Automation), is defined as full-Time performance by an automated driving system of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver. It is estimated that level 5 autonomous vehicles on public roads will help eliminate more than 90% [1] of the 35,000 annual traffic fatalities caused by human error in the United States [2]; reduce commute time, road congestion, and pollution; and increase driving resource utilization [3].
AB - The technical challenge of creating a self-driving vehicle remains an open problem despite significant advancements from universities, car manufacturers, and technology companies. Full autonomy, known as level 5 (see Society of Automotive Engineers Levels of Driving Automation), is defined as full-Time performance by an automated driving system of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver. It is estimated that level 5 autonomous vehicles on public roads will help eliminate more than 90% [1] of the 35,000 annual traffic fatalities caused by human error in the United States [2]; reduce commute time, road congestion, and pollution; and increase driving resource utilization [3].
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U2 - 10.1109/MCS.2018.2876958
DO - 10.1109/MCS.2018.2876958
M3 - Article
AN - SCOPUS:85060544913
SN - 1066-033X
VL - 39
SP - 26
EP - 55
JO - IEEE Control Systems
JF - IEEE Control Systems
IS - 1
M1 - 8616931
ER -