An Effective Method for Self-driving Car Navigation based on Lidar

Meng Liu; Yu Liu; Jianwei Niu; Yu Du; Yanchen Wan

Collaborative Computing: Networking, Applications and Worksharing. 13th International Conference, CollaborateCom 2017, Edinburgh, UK, December 11–13, 2017, Proceedings

Research Article

An Effective Method for Self-driving Car Navigation based on Lidar

Download

72 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-030-00916-8_65,
    author={Meng Liu and Yu Liu and Jianwei Niu and Yu Du and Yanchen Wan},
    title={An Effective Method for Self-driving Car Navigation based on Lidar},
    proceedings={Collaborative Computing: Networking, Applications and Worksharing. 13th International Conference, CollaborateCom 2017, Edinburgh, UK, December 11--13, 2017, Proceedings},
    proceedings_a={COLLABORATECOM},
    year={2018},
    month={10},
    keywords={Lidar Self-driving car LNA Navigation Linear regression},
    doi={10.1007/978-3-030-00916-8_65}
}

Meng Liu
Yu Liu
Jianwei Niu
Yu Du
Yanchen Wan
Year: 2018
An Effective Method for Self-driving Car Navigation based on Lidar
COLLABORATECOM
Springer
DOI: 10.1007/978-3-030-00916-8_65

Meng Liu¹^,*, Yu Liu¹, Jianwei Niu¹, Yu Du², Yanchen Wan¹

1: Beihang University
2: Beijing Union University

*Contact email: liumeng_scse@buaa.edu.cn

Abstract

Existing navigation methods are generally based on GPS or cameras and these methods have limitations in terms of signal strength and brightness. To overcome drawbacks of navigation methods above, we propose a Lidar-based Navigation Approach (LNA) to predict movement trajectory of self-driving vehicles through road edges information, and this approach is a fitting and real-time regression method. By combining regression model with vehicle coordinate system, navigation trajectory is accurately generated. Experiments on common road scenarios demonstrate that our approach is effective to improve navigation techniques.

Keywords: Lidar Self-driving car LNA Navigation Linear regression

Published: 2018-10-17
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-030-00916-8_65