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VI-Map: Infrastructure-Assisted Real-Time HD Mapping for Autonomous Driving.

Authors :
He, Yuze
Bian, Chen
Xia, Jingfei
Shi, Shuyao
Yan, Zhenyu
Song, Qun
Xing, Guoliang
Source :
MobiCom: International Conference on Mobile Computing & Networking; 2023, p1-15, 15p
Publication Year :
2023

Abstract

HD map is a key enabling technology towards fully autonomous driving. We propose VI-Map, the first system that leverages roadside infrastructure to enhance real-time HD mapping for autonomous driving. The core concept of VI-Map is to exploit the unique cumulative observations made by roadside infrastructure to build and maintain an accurate and current HD map. This HD map is then fused with on-vehicle HD maps in real time, resulting in a more comprehensive and up-to-date HD map. By extracting concise bird-eye-view features from infrastructure observations and utilizing vectorized map representations, VI-Map incurs low compute and communication overhead. We conducted end-to-end evaluations of VI-Map on a real-world testbed and a simulator. Experiment results show that VI-Map can construct decentimeter-level (up to 0.3 m) HD maps and achieve real-time (up to a delay of 42 ms) map fusion between driving vehicles and roadside infrastructure. This represents a significant improvement of 2.8× and 3× in map accuracy and coverage compared to the state-of-the-art online HD mapping approaches. A video demo of VI-Map on our real-world testbed is available at https://youtu.be/p2RO65R5Ezg. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15435679
Database :
Complementary Index
Journal :
MobiCom: International Conference on Mobile Computing & Networking
Publication Type :
Conference
Accession number :
180031868
Full Text :
https://doi.org/10.1145/3570361.3613280