IEICE TRANSACTIONS on Information
A Practical and Optimal Path Planning for Autonomous Parking Using Fast Marching Algorithm and Support Vector Machine
Summary :
This paper proposes a novel practical path planning framework for autonomous parking in cluttered environments with narrow passages. The proposed global path planning method is based on an improved Fast Marching algorithm to generate a path while considering the moving forward and backward maneuver. In addition, the Support Vector Machine is utilized to provide the maximum clearance from obstacles considering the vehicle dynamics to provide a safe and feasible path. The algorithm considers the most critical points in the map and the complexity of the algorithm is not affected by the shape of the obstacles. We also propose an autonomous parking scheme for different parking situation. The method is implemented on autonomous vehicle platform and validated in the real environment with narrow passages.
- Publication
- IEICE TRANSACTIONS on Information Vol.E96-D No.12 pp.2795-2804
- Publication Date
- 2013/12/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E96.D.2795
- Type of Manuscript
- PAPER
- Category
- Artificial Intelligence, Data Mining
Authors
Quoc Huy DO
Toyota Technological Institute
Seiichi MITA
Toyota Technological Institute
Keisuke YONEDA
Toyota Technological Institute
Keyword
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Quoc Huy DO, Seiichi MITA, Keisuke YONEDA, "A Practical and Optimal Path Planning for Autonomous Parking Using Fast Marching Algorithm and Support Vector Machine" in IEICE TRANSACTIONS on Information,
vol. E96-D, no. 12, pp. 2795-2804, December 2013, doi: 10.1587/transinf.E96.D.2795.
Abstract: This paper proposes a novel practical path planning framework for autonomous parking in cluttered environments with narrow passages. The proposed global path planning method is based on an improved Fast Marching algorithm to generate a path while considering the moving forward and backward maneuver. In addition, the Support Vector Machine is utilized to provide the maximum clearance from obstacles considering the vehicle dynamics to provide a safe and feasible path. The algorithm considers the most critical points in the map and the complexity of the algorithm is not affected by the shape of the obstacles. We also propose an autonomous parking scheme for different parking situation. The method is implemented on autonomous vehicle platform and validated in the real environment with narrow passages.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E96.D.2795/_p
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@ARTICLE{e96-d_12_2795,
author={Quoc Huy DO, Seiichi MITA, Keisuke YONEDA, },
journal={IEICE TRANSACTIONS on Information},
title={A Practical and Optimal Path Planning for Autonomous Parking Using Fast Marching Algorithm and Support Vector Machine},
year={2013},
volume={E96-D},
number={12},
pages={2795-2804},
abstract={This paper proposes a novel practical path planning framework for autonomous parking in cluttered environments with narrow passages. The proposed global path planning method is based on an improved Fast Marching algorithm to generate a path while considering the moving forward and backward maneuver. In addition, the Support Vector Machine is utilized to provide the maximum clearance from obstacles considering the vehicle dynamics to provide a safe and feasible path. The algorithm considers the most critical points in the map and the complexity of the algorithm is not affected by the shape of the obstacles. We also propose an autonomous parking scheme for different parking situation. The method is implemented on autonomous vehicle platform and validated in the real environment with narrow passages.},
keywords={},
doi={10.1587/transinf.E96.D.2795},
ISSN={1745-1361},
month={December},}
Copy
TY - JOUR
TI - A Practical and Optimal Path Planning for Autonomous Parking Using Fast Marching Algorithm and Support Vector Machine
T2 - IEICE TRANSACTIONS on Information
SP - 2795
EP - 2804
AU - Quoc Huy DO
AU - Seiichi MITA
AU - Keisuke YONEDA
PY - 2013
DO - 10.1587/transinf.E96.D.2795
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E96-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2013
AB - This paper proposes a novel practical path planning framework for autonomous parking in cluttered environments with narrow passages. The proposed global path planning method is based on an improved Fast Marching algorithm to generate a path while considering the moving forward and backward maneuver. In addition, the Support Vector Machine is utilized to provide the maximum clearance from obstacles considering the vehicle dynamics to provide a safe and feasible path. The algorithm considers the most critical points in the map and the complexity of the algorithm is not affected by the shape of the obstacles. We also propose an autonomous parking scheme for different parking situation. The method is implemented on autonomous vehicle platform and validated in the real environment with narrow passages.
ER -
English
