Laser Scanning Systems in Highway and Safety Assessment: Analysis of Highway Geometry and Safety Using LiDAR

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Laser Scanning Systems in Highway and Safety Assessment: Analysis of Highway Geometry and Safety Using LiDAR Authors: , Format: Hardback First Published: Published By: Springer Nature Switzerland AG Pages: 157 Illustrations and other contents: 76 Tables, color; XV, 157 p. Language: English ISBN: 9783030103736 Category:

This book aims to promote the core understanding of a proper modelling of road traffic accidents by Neural Networks (NN) using traffic information and road geometry delineated from laser scanning data. The first two chapters of the book introduce the reader to laser-scanning technology with creative explanation and graphical illustrations, review and recent methods of extracting geometric road parameters. The third and fourth chapter present an optimizing support vector machine, ensemble trees and a novel method for networks. After introducing the principles of neural networks in chapter 5 and reviewing recent studies on accident modelling by neural networks in chapter 6, this book goes on exploring the details of NN and the performance in predicting the traffic accidents and their comparison with common data mining models. Chapter 7 presents deep learning applications in modelling accident data using feedforward, convolutional, recurrent neural. Chapter 8 develops an injury severity prediction model using feedforward NN. Chapter 9 improves the injury severity prediction model by replacing the traditional feedforward NN by a Convolutional Neural Network. In chapter 10, a Recurrent Neural Network (RNN), which accounts for temporal structure inherent in the accident data. Chapter 11 presents a procedure for modelling traffic accident with little data based on the concept of Transfer Learning. Chapter 12 presents the comparative study between NN models, support vector machine, and logistic regression for injury severity prediction. Finally, the methods of quantifying the importance of accident related factors in NN models are presented in chapter 13. This book aims to help graduate students, professionals, decision makers, and road planners in developing better traffic accident prediction models using advanced neural networks.

Weight0.753 kg

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Author Biography

Prof. Dr. Biswajeet PradhanDistinguished Professor Biswajeet Pradhan is an internationally established scientist in the field of Geospatial Information Systems (GIS), remote sensing and image processing, complex modelling/geo-computing, machine learning and soft-computing applications, natural hazards and environmental modelling and remote sensing of Earth observation. He is the Director of the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS) at the Faculty of Engineering and IT. He is also the distinguished professor at the University of Technology, Sydney. He is listed as the World's most Highly Cited researcher by Clarivate Analytics Report in 2018, 2017 and 2016 as one of the world's most influential mind. In 2018, he has been awarded as World Class Professor by the Ministry of Research, Technology and Higher Education, Indonesia. He is a recipient of Alexander von Humboldt Research Fellowship from Germany. In 2011, he received his habilitation in "Remote Sensing" from Dresden University of Technology, Germany. Since February 2015, he is serving as "Ambassador Scientist" for Alexander Humboldt Foundation, Germany. Professor Pradhan has received 55 awards since 2006 in recognition of his excellence in teaching, service and research. Out of his more than 450 articles, more than 400 have been published in science citation index (SCI/SCIE) technical journals. He has written eight books and thirteen book chapters. He is the Associate Editor and Editorial Member in more than 8 ISI journals. Professor Pradhan has widely travelled abroad visiting more than 52 countries to present his research findings. Maher Ibrahim Sameen is a postdoctoral research fellow at the School of Information Systems and Modelling, UTS. He is fuelled by his passion for developing algorithms for remote sensing and geospatial applications. His background in surveying engineering, geomatics, and remote sensing inform his mindful but competitive approach. He has published over 19 journal articles indexed in Web of Science, attended 9 conferences, and won three awards.