TY - GEN
T1 - REITS
T2 - 22nd International Workshop on Mobile Computing Systems and Applications, HotMobile 2021
AU - Li, Zhuqi
AU - Wu, Can
AU - Wagner, Sigurd
AU - Sturm, James C.
AU - Verma, Naveen
AU - Jamieson, Kyle
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/2/24
Y1 - 2021/2/24
N2 - Autonomous vehicles are predicted to dominate the transportation industry in the foreseeable future. Safety is one of the major challenges to the early deployment of self-driving systems. To ensure safety, self-driving vehicles must sense and detect humans, other vehicles, and road infrastructure accurately, robustly, and timely. However, existing sensing techniques used by self-driving vehicles may not be absolutely reliable. In this paper, we design REITS, a system to improve the reliability of RF-based sensing modules for autonomous vehicles. We conduct theoretical analysis on possible failures of existing RF-based sensing systems. Based on the analysis, REITS adopts a multi-antenna design, which enables constructive blind beamforming to return an enhanced radar signal in the incident direction. REITS can also let the existing radar system sense identification information by switching between constructive beamforming state and destructive beamforming state. Preliminary results show that REITS improves the detection distance of a self-driving car radar by a factor of 3.63.
AB - Autonomous vehicles are predicted to dominate the transportation industry in the foreseeable future. Safety is one of the major challenges to the early deployment of self-driving systems. To ensure safety, self-driving vehicles must sense and detect humans, other vehicles, and road infrastructure accurately, robustly, and timely. However, existing sensing techniques used by self-driving vehicles may not be absolutely reliable. In this paper, we design REITS, a system to improve the reliability of RF-based sensing modules for autonomous vehicles. We conduct theoretical analysis on possible failures of existing RF-based sensing systems. Based on the analysis, REITS adopts a multi-antenna design, which enables constructive blind beamforming to return an enhanced radar signal in the incident direction. REITS can also let the existing radar system sense identification information by switching between constructive beamforming state and destructive beamforming state. Preliminary results show that REITS improves the detection distance of a self-driving car radar by a factor of 3.63.
KW - Robustness
KW - Self-driving car
KW - Surface
UR - http://www.scopus.com/inward/record.url?scp=85102082407&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102082407&partnerID=8YFLogxK
U2 - 10.1145/3446382.3448650
DO - 10.1145/3446382.3448650
M3 - Conference contribution
AN - SCOPUS:85102082407
T3 - HotMobile 2021 - Proceedings of the 22nd International Workshop on Mobile Computing Systems and Applications
SP - 78
EP - 84
BT - HotMobile 2021 - Proceedings of the 22nd International Workshop on Mobile Computing Systems and Applications
PB - Association for Computing Machinery, Inc
Y2 - 24 February 2021 through 26 February 2021
ER -