Dynamic and Safe Path Planning Based on Support Vector Machine among Multi Moving Obstacles for Autonomous Vehicles
Summary :
We propose a practical local and global path-planning algorithm for an autonomous vehicle or a car-like robot in an unknown semi-structured (or unstructured) environment, where obstacles are detected online by the vehicle's sensors. The algorithm utilizes a probabilistic method based on particle filters to estimate the dynamic obstacles' locations, a support vector machine to provide the critical points and Bezier curves to smooth the generated path. The generated path safely travels through various static and moving obstacles and satisfies the vehicle's movement constraints. The algorithm is implemented and verified on simulation software. Simulation results demonstrate the effectiveness of the proposed method in complicated scenarios that posit the existence of multi moving objects.
- Publication
- IEICE TRANSACTIONS on Information Vol.E96-D No.2 pp.314-328
- Publication Date
- 2013/02/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E96.D.314
- Type of Manuscript
- PAPER
- Category
- Artificial Intelligence, Data Mining
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Quoc Huy DO, Seiichi MITA, Hossein Tehrani Nik NEJAD, Long HAN, "Dynamic and Safe Path Planning Based on Support Vector Machine among Multi Moving Obstacles for Autonomous Vehicles" in IEICE TRANSACTIONS on Information,
vol. E96-D, no. 2, pp. 314-328, February 2013, doi: 10.1587/transinf.E96.D.314.
Abstract: We propose a practical local and global path-planning algorithm for an autonomous vehicle or a car-like robot in an unknown semi-structured (or unstructured) environment, where obstacles are detected online by the vehicle's sensors. The algorithm utilizes a probabilistic method based on particle filters to estimate the dynamic obstacles' locations, a support vector machine to provide the critical points and Bezier curves to smooth the generated path. The generated path safely travels through various static and moving obstacles and satisfies the vehicle's movement constraints. The algorithm is implemented and verified on simulation software. Simulation results demonstrate the effectiveness of the proposed method in complicated scenarios that posit the existence of multi moving objects.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E96.D.314/_p
Copy
@ARTICLE{e96-d_2_314,
author={Quoc Huy DO, Seiichi MITA, Hossein Tehrani Nik NEJAD, Long HAN, },
journal={IEICE TRANSACTIONS on Information},
title={Dynamic and Safe Path Planning Based on Support Vector Machine among Multi Moving Obstacles for Autonomous Vehicles},
year={2013},
volume={E96-D},
number={2},
pages={314-328},
abstract={We propose a practical local and global path-planning algorithm for an autonomous vehicle or a car-like robot in an unknown semi-structured (or unstructured) environment, where obstacles are detected online by the vehicle's sensors. The algorithm utilizes a probabilistic method based on particle filters to estimate the dynamic obstacles' locations, a support vector machine to provide the critical points and Bezier curves to smooth the generated path. The generated path safely travels through various static and moving obstacles and satisfies the vehicle's movement constraints. The algorithm is implemented and verified on simulation software. Simulation results demonstrate the effectiveness of the proposed method in complicated scenarios that posit the existence of multi moving objects.},
keywords={},
doi={10.1587/transinf.E96.D.314},
ISSN={1745-1361},
month={February},}
Copy
TY - JOUR
TI - Dynamic and Safe Path Planning Based on Support Vector Machine among Multi Moving Obstacles for Autonomous Vehicles
T2 - IEICE TRANSACTIONS on Information
SP - 314
EP - 328
AU - Quoc Huy DO
AU - Seiichi MITA
AU - Hossein Tehrani Nik NEJAD
AU - Long HAN
PY - 2013
DO - 10.1587/transinf.E96.D.314
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E96-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2013
AB - We propose a practical local and global path-planning algorithm for an autonomous vehicle or a car-like robot in an unknown semi-structured (or unstructured) environment, where obstacles are detected online by the vehicle's sensors. The algorithm utilizes a probabilistic method based on particle filters to estimate the dynamic obstacles' locations, a support vector machine to provide the critical points and Bezier curves to smooth the generated path. The generated path safely travels through various static and moving obstacles and satisfies the vehicle's movement constraints. The algorithm is implemented and verified on simulation software. Simulation results demonstrate the effectiveness of the proposed method in complicated scenarios that posit the existence of multi moving objects.
ER -
English
