Vehicle to Infrastructure-Based LiDAR Localization Method for Autonomous Vehicles
-
Published:2023-06-15
Issue:12
Volume:12
Page:2684
-
ISSN:2079-9292
-
Container-title:Electronics
-
language:en
-
Short-container-title:Electronics
Author:
Kim Myeong-jun1ORCID, Kwon Ohsung1, Kim Jungha2
Affiliation:
1. Graduate School of Automotive Engineering, Kookmin University, Seoul 02707, Republic of Korea 2. Department of Automotive and IT Convergence, Kookmin University, Seoul 02707, Republic of Korea
Abstract
The localization of autonomous vehicles using light detection and ranging (LiDAR) sensors relies on high-definition (HD) maps, which are essential for accurate positioning. However, the large storage capacity required for HD maps poses challenges for real-time performance. To address this issue, we propose a vehicle to infrastructure (V2I)-based LiDAR localization method. In this approach, real-time HD maps are transmitted to vehicles in the vicinity of the infrastructure, enabling localization without the need for map data. We conducted tests to determine the optimal size of the HD maps and the distance between vehicles and the infrastructure, considering the impact on transmission speed. Additionally, we compared the matching performance between the complete HD map and sub maps received from the infrastructure, to evaluate the effectiveness of our method in a qualitative manner.
Funder
National Research Foundation of Korea
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference27 articles.
1. Pendleton, S.D., Andersen, H., Du, X., Shen, X., Meghjani, M., Eng, Y.H., Rus, D., and Ang, M.H. (2017). Perception, Planning, Control, and Coordination for Autonomous Vehicles. Machines, 5. 2. Laconte, J., Kasmi, A., Aufrère, R., Vaidis, M., and Chapuis, R. (2022). A Survey of Localization Methods for Autonomous Vehicles in Highway Scenarios. Sensors, 22. 3. Real-time localization method for autonomous vehicle using 3DLIDAR;Zhang;Dyn. Veh. Roads Tracks,2017 4. Heuristic Monte Carlo Algorithm for Unmanned Ground Vehicles Realtime Localization and Mapping;Chen;IEEE Trans. Veh. Technol.,2020 5. Jo, K., Keonyup, C., and Myoungho, S. (2013, January 23–26). GPS-bias correction for precise localization of autonomous vehicles. Proceedings of the 2013 IEEE Intelligent Vehicles Symposium (IV), Gold Coast, QLD, Australia.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|