@inproceedings{0d2a8ea9ca6140ddb01ea487cfa718ba,
title = "Real-time localization method for autonomous vehicle using 3D-LIDAR",
abstract = "Precise and robust localization is a significant task for autonomous vehicles in complex scenarios. In this paper, a novel method is proposed to precisely locate the autonomous vehicle using a 3D-LIDAR sensor. The curb-based feature matching and intensity-based feature matching results are fused to obtain an accurate estimated position. A curb detection method is proposed to extract the curb position and an area probability searching method is proposed to match the intensity feature. Experimental results demonstrate the accuracy and robustness of the proposed method.",
author = "Yihuan Zhang and Liang Wang and Jun Wang and Dolan, {John M.}",
note = "Publisher Copyright: {\textcopyright} 2018 Taylor & Francis Group, London UK.; 25th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2017 ; Conference date: 14-08-2017 Through 18-08-2017",
year = "2018",
language = "English",
isbn = "9781138035713",
series = "The Dynamics of Vehicles on Roads and Tracks",
publisher = "CRC Press/Balkema",
pages = "271--276",
editor = "Maksym Spiryagin and Cole Cole and Tim McSweeney and Timothy Gordon",
booktitle = "The Dynamics of Vehicles on Roads and Tracks",
}