Road Terrain Classification Technology for Autonomous Vehicle
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Beschreibung
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.
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.
Comprehensively discusses various accelerometers, cameras, sensors, and LRFs for autonomous vehicles Provides an extensive review of road terrain classification by applying the MRF multiple-sensor fusion method Includes detailed comparisons of tables and figures, confirming the MRF multiple-sensor fusion method’s effectiveness and feasibility for road terrain classification
Autor*in
Shifeng Wang
Themen in »Road Terrain Classification Technology for Autonomous Vehicle«
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