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Sensors 2016, 16(7), 1123; doi:10.3390/s16071123

Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner

1
School of Electrical and Electronic Engineering, Yonsei University, 50 Seodaemun-gu Sinchon-dong, Seoul 120-743, Korea
2
School of Electrical and Electronics Engineering, Chung-Ang University, 84 Heukseok-Ro Dongjak-Gu, Seoul 156-756, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 21 April 2016 / Revised: 14 July 2016 / Accepted: 15 July 2016 / Published: 20 July 2016
View Full-Text   |   Download PDF [4349 KB, uploaded 20 July 2016]   |  

Abstract

There are several types of intersections such as merge-roads, diverge-roads, plus-shape intersections and two types of T-shape junctions in urban roads. When an autonomous vehicle encounters new intersections, it is crucial to recognize the types of intersections for safe navigation. In this paper, a novel intersection type recognition method is proposed for an autonomous vehicle using a multi-layer laser scanner. The proposed method consists of two steps: (1) static local coordinate occupancy grid map (SLOGM) building and (2) intersection classification. In the first step, the SLOGM is built relative to the local coordinate using the dynamic binary Bayes filter. In the second step, the SLOGM is used as an attribute for the classification. The proposed method is applied to a real-world environment and its validity is demonstrated through experimentation. View Full-Text
Keywords: multi-laser scanner; intersections; recognition; local coordinate; occupancy grid map; static map multi-laser scanner; intersections; recognition; local coordinate; occupancy grid map; static map
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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An, J.; Choi, B.; Sim, K.-B.; Kim, E. Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner. Sensors 2016, 16, 1123.

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