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Road terrain classification technolo...

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Road terrain classification technology for autonomous vehicle

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Road terrain classification technology for autonomous vehicleby Shifeng Wang.
作者:	Wang, Shifeng.
出版者:	Singapore :Springer Singapore :2019.
面頁冊數:	xvi, 97 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Autonomous vehicles.
電子資源:	https://doi.org/10.1007/978-981-13-6155-5
ISBN:	9789811361555$q(electronic bk.)

Road terrain classification technology for autonomous vehicle
Wang, Shifeng.

Road terrain classification technology for autonomous vehicle[electronic resource] /by Shifeng Wang. - Singapore :Springer Singapore :2019. - xvi, 97 p. :ill., digital ;24 cm. - Unmanned system technologies,2523-3734. - Unmanned system technologies..

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.

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.

ISBN: 9789811361555$q(electronic bk.)

Standard No.: 10.1007/978-981-13-6155-5doiSubjects--Topical Terms:

736853
Autonomous vehicles.

LC Class. No.: TL152.8

Dewey Class. No.: 629.046

Road terrain classification technology for autonomous vehicle
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520 $a 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.
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