Paper Info
Title
An Effective Method for Self-driving Car Navigation based on Lidar.
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.
Year
DOI
Venue
2017
10.1007/978-3-030-00916-8_65
Lecture Notes of the Institute for Computer Sciences, Social Informatics, and Telecommunications Engineering
Keywords
Field
DocType
Lidar,Self-driving car,LNA,Navigation,Linear regression
Coordinate system,Computer vision,Computer science,Regression analysis,Effective method,Lidar,Global Positioning System,Artificial intelligence,Brightness,Trajectory,Distributed computing,Linear regression
Conference
Volume
ISSN
Citations 
252
1867-8211
0
PageRank 
References 
Authors
0.34
8
5
Name
Order
Citations
PageRank
Meng Liu13918.70
Yu Liu2347.67
Jianwei Niu31643141.54
Yu Du400.34
Yanchen Wan500.68