Road Terrain Classification Technology for Autonomous Vehicle

  • Shifeng Wang

Part of the Unmanned System Technologies book series (UST)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Shifeng Wang
    Pages 1-5
  3. Shifeng Wang
    Pages 7-19
  4. Shifeng Wang
    Pages 55-68
  5. Shifeng Wang
    Pages 69-78
  6. Shifeng Wang
    Pages 95-96
  7. Back Matter
    Pages 97-97

About this book


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. 


Mutiple Sensor Laser Range Finder Principal Component Analysis Power Spectral Density Fast Fourier Transform Support Vector Machine Markov Random Field Grey-Level Co-occurrence Matrix

Authors and affiliations

  • Shifeng Wang
    • 1
  1. 1.School of Optoelectronic EngineeringChangchun University of Science and TechnologyChangchunChina

Bibliographic information

  • DOI
  • Copyright Information China Machine Press, Beijing and Springer Nature Singapore Pte Ltd. 2019
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering
  • Print ISBN 978-981-13-6154-8
  • Online ISBN 978-981-13-6155-5
  • Series Print ISSN 2523-3734
  • Series Online ISSN 2523-3742
  • Buy this book on publisher's site