Laser Scanning Systems in Highway and Safety Assessment

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117,69 

Analysis of Highway Geometry and Safety Using LiDAR, Advances in Science, Technology & Innovation

ISBN: 3030103730
ISBN 13: 9783030103736
Autor: Pradhan, Biswajeet/Ibrahim Sameen, Maher
Verlag: Springer Verlag GmbH
Umfang: xv, 157 S.
Erscheinungsdatum: 18.04.2019
Auflage: 1/2020
Produktform: Gebunden/Hardback
Einband: Gebunden

This book aims to promote the core understanding of a proper modelling of road traffic accidents by deep learning methods 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 next three chapters present different machine learning and statistical techniques applied to extract road geometry information from laser scanning data. Chapters 6 and 7 present methods for modelling roadside features and automatic road geometry identification in vector data. After that, this book goes on reviewing methods used for road traffic accident modelling including accident frequency and injury severity of the traffic accident (Chapter 8). Then, the next chapter explores the details of neural networks and their performance in predicting the traffic accidents along with a comparison with common data mining models. Chapter 10 presents a novel hybrid model combining extreme gradient boosting and deep neural networks for predicting injury severity of road traffic accidents. This chapter is followed by deep learning applications in modelling accident data using feed-forward, convolutional, recurrent neural network models (Chapter 11). The final chapter (Chapter 12) presents a procedure for modelling traffic accident with little data based on the concept of transfer learning. This book aims to help graduate students, professionals, decision makers, and road planners in developing better traffic accident prediction models using advanced neural networks.

Artikelnummer: 5976463 Kategorie:

Beschreibung

Presents an overview of laser scanning technology in the context of road geometry modelling Includes a comprehensive review on road geometry modelling and traffic accident prediction with neural networks Introduces neural networks with simple theoretical backgrounds and creative illustration Contains special chapters on novel deep learning models developed for predicting traffic accidents Includes a comparative study between neural networks and statistical methods

Autorenporträt

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 Worlds most Highly Cited researcher by Clarivate Analytics Report in 2018, 2017 and 2016 as one of the worlds 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 habilitationin 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 hismindful but competitive approach. He has published over 19 journal articles indexed in Web of Science, attended 9 conferences, and won three awards. 

Herstellerkennzeichnung:


Springer Verlag GmbH
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69121 Heidelberg
DE

E-Mail: juergen.hartmann@springer.com

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