TY - GEN
T1 - Brief industry paper
T2 - 27th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2021
AU - Xie, Jinliang
AU - Tang, Jie
AU - Wang, Yanzhi
AU - Zhu, Qi
AU - Liu, Shaoshan
N1 - Funding Information:
ACKNOWLEDGMENT This work is supported by Guangdong R&D Key Project of China under Grant No.2018B010107003, Doctoral Startup Program of Guangdong Natural Science Foundation under Grant No.2018A030310408. Jie Tang is the corresponding author of this paper.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/5
Y1 - 2021/5
N2 - As a fundamental component in the autonomous driving technology stack, High Definition Maps (HD map) provide high-precision descriptions of the environment. It enables extremely accurate perception and localization while improving the efficiency of path planning. However, the HD map's extremely large data volume poses great challenges for the real-time and safety requirements of autonomous driving. Based on our real-world deployment experiences, we first demonstrate how the existing data transmission mechanism is weak in supporting HD map services. To address this problem, we propose an HD map data service mechanism on top of Vehicle-to-Infrastructure (V2I) data transmission under a tight time and energy budget. By this mechanism, the selected road side unit (RSU) nodes cooperate on map provisioning tasks and transmit HD map data proportionately. Furthermore, we model the real-time map data service into a partial knapsack problem and develop a greedy data transmission algorithm. Experimental results confirm that the proposed mechanism can ensure the real-time HD map data service meanwhile meeting the energy limits.
AB - As a fundamental component in the autonomous driving technology stack, High Definition Maps (HD map) provide high-precision descriptions of the environment. It enables extremely accurate perception and localization while improving the efficiency of path planning. However, the HD map's extremely large data volume poses great challenges for the real-time and safety requirements of autonomous driving. Based on our real-world deployment experiences, we first demonstrate how the existing data transmission mechanism is weak in supporting HD map services. To address this problem, we propose an HD map data service mechanism on top of Vehicle-to-Infrastructure (V2I) data transmission under a tight time and energy budget. By this mechanism, the selected road side unit (RSU) nodes cooperate on map provisioning tasks and transmit HD map data proportionately. Furthermore, we model the real-time map data service into a partial knapsack problem and develop a greedy data transmission algorithm. Experimental results confirm that the proposed mechanism can ensure the real-time HD map data service meanwhile meeting the energy limits.
KW - Autonomous driving
KW - Energy Efficiency
KW - HD Maps
KW - Map Data distribution
KW - Map Data provisioning
UR - http://www.scopus.com/inward/record.url?scp=85113732418&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113732418&partnerID=8YFLogxK
U2 - 10.1109/RTAS52030.2021.00042
DO - 10.1109/RTAS52030.2021.00042
M3 - Conference contribution
AN - SCOPUS:85113732418
T3 - Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS
SP - 421
EP - 424
BT - Proceedings - 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 18 May 2021 through 21 May 2021
ER -
