Chapter
Jun 29, 2016
Clustering-Based Lateral Longitudinal Target Recognition of In-Vehicle LIDAR Data
Authors: Chao Deng [email protected], Chaozhong Wu [email protected], Nengchao Lyu [email protected], and Ze Li [email protected]Author Affiliations
Publication: CICTP 2016
Abstract
In order to improve the accuracy of lateral and vertical target recognition in a car-following situation, the box plot is used to analyze and filter discrete points to overcome the LIDAR point data error; application of the modified adaptive K-means clustering algorithm which is based on the clustering evaluation index is applied to process the LIDAR point from LUX4; the candidate targets are output by clustering results. The test results show that the obstacle detection algorithm is more robust and reliable in the car-following situation.
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Published In
CICTP 2016
Pages: 308 - 321
Copyright
© 2016 American Society of Civil Engineers.
History
Published online: Jun 29, 2016
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Authors
Affiliations
Intelligent Transportation Systems Research Center, Wuhan Univ. of Technology, Wuhan 430063, China. E-mail: [email protected]
Chaozhong Wu [email protected]
Professor, Intelligent Transportation Systems Research Center, Wuhan Univ. of Technology, Wuhan 430063, China. E-mail: [email protected]
Associate Professor, Intelligent Transportation Systems Research Center, Wuhan Univ. of Technology, Wuhan 430063, China. E-mail: [email protected]
Intelligent Transportation Systems Research Center, Wuhan Univ. of Technology, Wuhan 430063, China. E-mail: [email protected]
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