Brief industry paper: An infrastructure-aided high definition map data provisioning service for autonomous driving

Jinliang Xie; Jie Tang; Yanzhi Wang; Qi Zhu; Shaoshan Liu

doi:10.1109/RTAS52030.2021.00042

Brief industry paper: An infrastructure-aided high definition map data provisioning service for autonomous driving

Jinliang Xie, Jie Tang, Yanzhi Wang, Qi Zhu, Shaoshan Liu

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

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.

Original language	English (US)
Title of host publication	Proceedings - 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	421-424
Number of pages	4
ISBN (Electronic)	9781665403863
DOIs	https://doi.org/10.1109/RTAS52030.2021.00042
State	Published - May 2021
Event	27th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2021 - Virtual, Online Duration: May 18 2021 → May 21 2021

Publication series

Name	Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS
Volume	2021-May
ISSN (Print)	1545-3421

Conference

Conference	27th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2021
City	Virtual, Online
Period	5/18/21 → 5/21/21

Funding

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.

Keywords

Autonomous driving
Energy Efficiency
HD Maps
Map Data distribution
Map Data provisioning

ASJC Scopus subject areas

General Engineering

Access to Document

10.1109/RTAS52030.2021.00042

Cite this

Xie, J., Tang, J., Wang, Y., Zhu, Q., & Liu, S. (2021). Brief industry paper: An infrastructure-aided high definition map data provisioning service for autonomous driving. In Proceedings - 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021 (pp. 421-424). Article 9470492 (Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS; Vol. 2021-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTAS52030.2021.00042

Xie, Jinliang ; Tang, Jie ; Wang, Yanzhi et al. / Brief industry paper : An infrastructure-aided high definition map data provisioning service for autonomous driving. Proceedings - 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 421-424 (Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS).

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title = "Brief industry paper: An infrastructure-aided high definition map data provisioning service for autonomous driving",

abstract = "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.",

keywords = "Autonomous driving, Energy Efficiency, HD Maps, Map Data distribution, Map Data provisioning",

author = "Jinliang Xie and Jie Tang and Yanzhi Wang and Qi Zhu and Shaoshan Liu",

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Xie, J, Tang, J, Wang, Y, Zhu, Q & Liu, S 2021, Brief industry paper: An infrastructure-aided high definition map data provisioning service for autonomous driving. in Proceedings - 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021., 9470492, Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS, vol. 2021-May, Institute of Electrical and Electronics Engineers Inc., pp. 421-424, 27th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2021, Virtual, Online, 5/18/21. https://doi.org/10.1109/RTAS52030.2021.00042

Brief industry paper: An infrastructure-aided high definition map data provisioning service for autonomous driving. / Xie, Jinliang; Tang, Jie; Wang, Yanzhi et al.
Proceedings - 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 421-424 9470492 (Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS; Vol. 2021-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Tang, Jie

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AU - Zhu, Qi

AU - Liu, Shaoshan

PY - 2021/5

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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.

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KW - Energy Efficiency

KW - HD Maps

KW - Map Data distribution

KW - Map Data provisioning

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Xie J, Tang J, Wang Y, Zhu Q, Liu S. Brief industry paper: An infrastructure-aided high definition map data provisioning service for autonomous driving. In Proceedings - 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 421-424. 9470492. (Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS). doi: 10.1109/RTAS52030.2021.00042

Brief industry paper: An infrastructure-aided high definition map data provisioning service for autonomous driving

Abstract

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Conference

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Keywords

ASJC Scopus subject areas

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