NDLI: Road and obstacle detection based on multi-layer laser radar in driverless car

Content Provider	IEEE Xplore Digital Library
Author	Duan Jianmin Zheng Kaihua Shi Lixiao
Copyright Year	2015
Description	Author affiliation: Acad. of Control Sci. & Eng., Beijing Univ. of Technol., Beijing, China (Duan Jianmin; Zheng Kaihua; Shi Lixiao)
Abstract	To make a driverless car with better environment awareness, multi-layer laser radar was applied to detect roads and obstacles. Firstly the road edge data set was extracted from numerous laser radar data based on characteristics of the road edge data, and the cluster analysis of the data sets was done with the improved COBWEB algorithm based on Euclidean distance. In order to divide the road into drivable area and undrivable area, the left and right road edges were respectively fitted into a straight line with the least squares method. Secondly DSmT was applied to establish a grid map for the environment, and dynamic obstacles were detected by the conflict coefficient within drivable area. Finally, the cluster analysis and information extraction of dynamic obstacles was completed by the expansion algorithm, erosion algorithm and improved eight neighborhood labeling algorithm. The results show that the algorithm can significantly reduce redundant operations and improve efficiency.
Starting Page	8003
Ending Page	8008
File Size	443172
Page Count	6
File Format	PDF
ISBN	9789881563897
ISSN	19341768
DOI	10.1109/ChiCC.2015.7260912
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Technical Committee on Control Theory, Chinese Association of Automation
Subject Keyword	Laser radar COBWEB algorithm Roads Heuristic algorithms Image edge detection Clustering algorithms Multi-layer laser radar DSmT Driverless car Euclidean distance Grid map Vehicle dynamics
Content Type	Text
Resource Type	Article

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