Editors:
- Reports on applications of big data and analytics in transportation modeling and traffic management
- Covers a wide range of topics, from optimization to assessment of safety and mobility
- Describes effective data-driven methods for modeling transportation
- Addresses the implications associated to digitization and cyber security
Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 879)
Conference series link(s): CSUM: Conference on Sustainable Urban Mobility
Conference proceedings info: CSUM 2018.
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Table of contents (105 papers)
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Front Matter
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Data-Driven Infrastructure Management
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Front Matter
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Transport Data and Analytics
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Front Matter
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About this book
Keywords
- Big Data for Mobility
- Eco-Driving Systems
- Evaluating Emissions Impact
- Connected and Autonomous Vehicles
- Electric Mobility
- Floating Data
- Traffic Safety Assessment
- ITS for Sustainable Development
- Travel Demand Prediction
- Traffic Flow Estimation
- Traffic Simulation
- Improving Mobility Experience
- Modeling Urban Transportation Networks
- Soft Transport Policy Measures
- GLOSA-Algorithms Applications
- Demand Responsive Systems
- Blockchain Infrastructure for Transportation
- Cycling and Walking Data Analysis
- Geo-positioning and Geo-information in Transportation Planning
- Smart Logistics Measures
Editors and Affiliations
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Department of Civil Engineering, Traffic, Transportation and Logistics Laboratory (TTLog), University of Thessaly, Volos, Greece
Eftihia G. Nathanail, Ioannis D. Karakikes
Bibliographic Information
Book Title: Data Analytics: Paving the Way to Sustainable Urban Mobility
Book Subtitle: Proceedings of 4th Conference on Sustainable Urban Mobility (CSUM2018), 24 - 25 May, Skiathos Island, Greece
Editors: Eftihia G. Nathanail, Ioannis D. Karakikes
Series Title: Advances in Intelligent Systems and Computing
DOI: https://doi.org/10.1007/978-3-030-02305-8
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-02304-1Published: 12 December 2018
eBook ISBN: 978-3-030-02305-8Published: 11 December 2018
Series ISSN: 2194-5357
Series E-ISSN: 2194-5365
Edition Number: 1
Number of Pages: XXI, 868
Number of Illustrations: 36 b/w illustrations, 199 illustrations in colour
Topics: Transportation Technology and Traffic Engineering, Data Mining and Knowledge Discovery, Sustainable Development, Energy Policy, Economics and Management