عنوان
پدید آورنده
موضوع
رده
TL152.8 .W36 2019
TL152
.
8
.
W36
2019
کتابخانه
محل استقرار
INTERNATIONAL STANDARD BOOK NUMBER
(Number (ISBN
9789811361555
(Number (ISBN
9789811361562
(Number (ISBN
9789811361579
(Number (ISBN
981136155X
(Number (ISBN
9811361568
(Number (ISBN
9811361576
Erroneous ISBN
9789811361548
Erroneous ISBN
9811361541
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Road terrain classification technology for autonomous vehicle /
General Material Designation
[Book]
First Statement of Responsibility
Shifeng Wang.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Singapore :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
[2019]
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource
SERIES
Series Title
Unmanned system technologies
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index.
CONTENTS NOTE
Text of Note
Intro; Preface; Contents; Abbreviations; List of Figures; List of Tables; 1 Introduction; 1.1 Background; 1.2 Motivation; 1.3 Overview; References; 2 Review of Related Work; 2.1 Accelerometer Applications; 2.1.1 Small-Sized Rover Platform Using Accelerometer; 2.1.2 Road Vehicle Using Accelerometer; 2.2 Camera Applications; 2.2.1 Small-Sized Rover Using Camera; 2.2.2 Road Vehicle Using Camera; 2.3 LRF Applications; 2.3.1 Small-Sized Rover Using LRF; 2.3.2 Road Vehicle Using LRF; 2.4 Mutiple-sensor Applications; 2.4.1 Small-Sized Rover Using Multiple Sensors
Text of Note
2.4.2 Road Vehicle Using Multiple Sensors2.5 Conclusion; References; 3 Acceleration-Based Road Terrain Classification; 3.1 Road Profile Estimation; 3.1.1 Acceleration (acc-t); 3.1.2 Quarter Vehicle Model (acc-t to y-t); 3.1.3 Vertical Displacement (y-t); 3.1.4 Speed (v-t); 3.1.5 Speed to Displacement (v-t to x-t); 3.1.6 Road Profile (y-x); 3.2 Features Extraction; 3.2.1 FFT Feature Extracted from Road Profile (y-x); 3.2.2 FFT Feature Extracted from Acceleration (acc-t); 3.2.3 Fast Wavelet Transform Feature Extracted from Acceleration (acc-t) and Road Profile (y-x); 3.3 Normalization
Text of Note
3.4 Principal Component Analysis3.5 K-Fold Cross-Validation; 3.6 Alternative Classifiers; 3.6.1 Naïve Bayes Classifier; 3.6.2 Neural Network Classifier; 3.6.3 Support Vector Machines Classifier; 3.7 Experiment; 3.7.1 Experiment Platform; 3.7.2 Acceleration-Based Experiments; 3.8 Experiment Results; 3.8.1 Feature Selection; 3.8.2 Speed Dependency; 3.8.3 Classifiers Selection; 3.8.4 Acceleration-Based Experiment Result; 3.9 Conclusion; References; 4 Image-Based Road Terrain Classification; 4.1 Texture Features from Image; 4.2 Image Feature Matrix Establishment
Text of Note
4.2.1 Grey-Level Co-occurrence Matrix4.2.2 Feature Extraction and Feature Matrix Formation; 4.3 Experiment; 4.3.1 Experimental Platform; 4.3.2 Image-Based Experiments; 4.4 Experiment Results; 4.5 Conclusion; References; 5 LRF-Based Road Terrain Classification; 5.1 Geometric Arrangement of the LRF; 5.2 Reconstruction of the Road Surface; 5.2.1 Range Data Processing; 5.2.2 Speed Data Processing; 5.2.3 Road Surface; 5.3 Feature Matrix; 5.4 Experiment; 5.4.1 Experimental Platform; 5.4.2 LRF-Based Experiments; 5.5 Experiment Results; 5.5.1 Speed Independency; 5.5.2 LRF-Based Experiment
Text of Note
5.6 ConclusionReferences; 6 Multiple-Sensor Based Road Terrain Classification; 6.1 Predicting LRF-Based Probe; 6.2 Markov Random Field; 6.2.1 Conditional Independence Properties; 6.2.2 Factorization Properties; 6.3 Establishment of MRF Application; 6.3.1 Nodes in MRF; 6.3.2 Variable Values of Nodes in MRF; 6.3.3 Clique Potentials in MRF; 6.3.4 Values of Clique Potentials in MRF; 6.3.5 Energy Function; 6.3.6 Optimization; 6.4 Experiment; 6.4.1 Experimental Platform; 6.4.2 Multiple-Sensor Fusion Based Experiment; 6.5 Experiment Results; 6.6 Conclusion; References; 7 Summary; 7.1 Conclusion
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8
8
8
8
SUMMARY OR ABSTRACT
Text of Note
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.
ACQUISITION INFORMATION NOTE
Source for Acquisition/Subscription Address
Springer Nature
Stock Number
com.springer.onix.9789811361555
OTHER EDITION IN ANOTHER MEDIUM
Title
Road terrain classification technology for autonomous vehicle.
International Standard Book Number
9789811361548
TOPICAL NAME USED AS SUBJECT
Automated vehicles.
Automated vehicles.
TECHNOLOGY & ENGINEERING-- Engineering (General)
(SUBJECT CATEGORY (Provisional
TEC-- 009000
TRC
TRC
TRCS
DEWEY DECIMAL CLASSIFICATION
Number
629
.
046
Edition
23
LIBRARY OF CONGRESS CLASSIFICATION
Class number
TL152
.
8
Book number
.
W36
2019
PERSONAL NAME - PRIMARY RESPONSIBILITY
Wang, Shifeng
ORIGINATING SOURCE
Date of Transaction
20200823233538.0
Cataloguing Rules (Descriptive Conventions))
pn
ELECTRONIC LOCATION AND ACCESS
Electronic name
مطالعه متن کتاب [Book]
Y
