Mobility Patterns, Big Data and Transport Analytics - 1st Edition - ISBN: 9780128129708

Mobility Patterns, Big Data and Transport Analytics

1st Edition

Tools and Applications for Modeling

Editors: Constantinos Antoniou Loukas Dimitriou Francisco Pereira
Paperback ISBN: 9780128129708
Imprint: Elsevier
Published Date: 1st September 2018
Page Count: 448
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Description

Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications and concepts in mobility analysis and transportation systems. Users will find a detailed, mobility ‘structural’ analysis and a look at the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications and transportation systems analysis that are related to complex processes and phenomena.

This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data’s impact on mobility and an introduction to the tools necessary to apply new techniques.

The book covers in detail, mobility ‘structural’ analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data’s impact on mobility, and an introduction to the tools necessary to apply new techniques.

Key Features

  • Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics
  • Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends
  • Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field
  • Captures and manages mobility patterns, covering multiple purposes and alternative transport modes, in a multi-disciplinary approach
  • Companion website features videos showing the analyses performed, as well as test codes and data-sets, allowing readers to recreate the presented analyses and apply the highlighted techniques to their own data

Readership

Transport researchers, practitioners, and consultants, Undergraduate and graduate students in transportation programs, Transport policy makers

Table of Contents

Part A Front matter
1. Introduction

Part B Theoretical underpinnings
2. Machine learning fundamentals
3. Combining Theory-driven and Data-driven Methods
4. Big Data Is not just a New Type, but a New Paradigm
5. Big Data Preparation Challenges and Tools
6. Data Science and Data Visualization

Part C Methodological
7. Social Networks Formations in Transport Demand Analysis
8. Human Mobility Patterns
9. Crowd-sourced data and users’ participation
10. Machine Learning Mechanisms for Augmenting Mobility Information
11. Model Based Machine Learning for the Transportation domain

Part D Application Domains
12. Capturing Mobility by Open-Data
13. Traffic Estimation Models in the Large-Scale
14. Big Data Applications in Transit Systems
15. Combining Information for Estimating Transit Ridership
16. Big Data Applications in Road Safety
17. The Mobile Society: Emerging Practices in the Travel Domain
18. Big Data in Infrastructure Management
19. Privacy and security
20. Cooperative Positioning for Urban Intelligent Transportation Systems (ITS) and Personal Mobility (PM): Challenges and Solutions

Part E Conclusions and Foresight
21. Conclusions/outlook

Details

No. of pages:
448
Language:
English
Copyright:
© Elsevier 2019
Published:
Imprint:
Elsevier
Paperback ISBN:
9780128129708

About the Editor

Constantinos Antoniou

Constantinos Antoniou is a Professor and Chair of Transportation Systems Engineering at the Technical University of Munich, Germany. He was previously an Associate Professor at the National Technical University of Athens, Greece. His research focuses on modelling and simulation of transportation systems, Intelligent Transport Systems (ITS), calibration and optimization applications, road safety and sustainable transport system. Antoniou has been involved in a large number of projects, primarily in Europe and the US, and has authored more than 250 scientific publications, including in Elsevier’s Transportation Research Part C: Emerging Technologies (for which he serves on the editorial board), and Journal of Transport Geography. He has also authored a book on dynamic traffic assignment models

Affiliations and Expertise

Professor and Chair of Transportation Systems Engineering, Technical University of Munich, Germany

Loukas Dimitriou

Dr. Loukas Dimitriou (from 2014) he is appointed Lecturer, in the Dept. of Civil and Environmental Engineering, University of Cyprus, Nicosia, Cyprus and Chair of Laboratory of Transportation Engineering. He holds a Diploma in Civil Engineering from National Technical University of Athens (NTUA) and a Ph.D. from Dept. of Transportation Planning and Engineering, NTUA. For the period 2011-2013 he was appointed Assistant Professor at King Saud University, School of Civil Engineering, Prince Mohamed bin Naif Chair for Traffic Safety Research, Riyadh, Saudi Arabia. His academic and professional activities relates to the analysis of travel demand, the use of advanced methods and techniques for optimizing transportation systems' design and in developing frameworks for supporting decisions in his fields. Research Interests: Transport Infrastructure Planning and Design Traffic Engineering Transportation Networks Competitive Design Demand Analysis and Forecasting Intelligent Transport Systems Transit Systems Terminals Highway Design Pedestrian Systems

Affiliations and Expertise

Dr., lecturer, Department of Civil and Environmental Engineering, University of Cyprus and Head, Lab. for Transport Engineering, University of Cyprus

Francisco Pereira

Francisco Pereira is a Professor at the Technical University of Denmark, in Kongens Lyngby, Denmark, where he leads the Smart Mobility research group. Previously, he was Senior Research Scientist at MIT/CEE ITSLab, where he worked on real-time traffic prediction, behavior modeling, and advanced data collection technologies, both in Boston and Singapore, as part of the Singapore-MIT Alliance for Research and Technology, Future Urban Mobility project (SMART/FM). His main research focus is on applying machine learning and pattern recognition to the context of transportation systems with the purpose of understanding and predicting mobility behavior, and modeling and optimizing the transportation system as a whole. He has been published in many journals, including in Elsevier’s Transportation Research Part C: Emerging Technologies.

Affiliations and Expertise

Professor, Technical University of Denmark, Kongens Lyngby, Denmark

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