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Road Terrain Classification Technology for Autonomous Vehicle
Author
Title
Road Terrain Classification Technology for Autonomous Vehicle [electronic resource] / by Shifeng Wang.
ISBN
9789811361555
Publication
Singapore : Springer Singapore : Imprint: Springer, 2019.
Physical Description
1 online resource (XVI, 97 p.) 43 illus., 32 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This book provides cutting-edge insights into autonomous vehicles and road terrain classification, and introduces a more rational and practical method for identifying road terrain. It presents the MRF algorithm, which combines the various sensors’ classification results to improve the forward LRF for predicting upcoming road terrain types. The comparison between the predicting LRF and its corresponding MRF show that the MRF multiple-sensor fusion method is extremely robust and effective in terms of classifying road terrain. The book also demonstrates numerous applications of road terrain classification for various environments and types of autonomous vehicle, and includes abundant illustrations and models to make the comparison tables and figures more accessible. .
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
April 01, 2019
Series
Unmanned System Technologies,
Contents
Introduction
Review of Related Work
Acceleration Based Road Terrain Classification
Image Based Road Terrain Classification
LRF Based Road Terrain Classification
Multiple-Sensor Based Road Terrain Classification
Conclusion and Future Direction.
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SpringerLink (Online service)
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