Lane-level Positioning based on 3D Tracking Path of Traffic Signs

Sung-ju Kim, Soon-Yong Park

2016

Abstract

Lane-level vehicle positioning is an important task for enhancing the accuracy of in-vehicle navigation systems and the safety of autonomous vehicles. GPS (Global Positioning System) or DGPS (Differential GPS) techniques are generally used in lane-level poisoning systems, which only provide an accuracy level up to 2-3 m. In this paper, we introduce a vision based lane-level positioning technique that provides more accurate prediction results. The proposed method predicts the current driving lane of the vehicle by tracking the 3D location of the traffic signs that are in the side-way of the road using a stereo camera. Several experiments are conducted to analyse the feasibility of the proposed method in driving lane level prediction. According to the experimental results, the proposed method could achieve 90.9% accuracy.

Paper Citation

in Harvard Style

Kim S. and Park S. (2016). Lane-level Positioning based on 3D Tracking Path of Traffic Signs . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 642-648. DOI: 10.5220/0005721106420648

in Bibtex Style

@conference{visapp16,
author={Sung-ju Kim and Soon-Yong Park},
title={Lane-level Positioning based on 3D Tracking Path of Traffic Signs},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={642-648},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005721106420648},
isbn={978-989-758-175-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Lane-level Positioning based on 3D Tracking Path of Traffic Signs
SN - 978-989-758-175-5
AU - Kim S.
AU - Park S.
PY - 2016
SP - 642
EP - 648
DO - 10.5220/0005721106420648