Overview
- Presents recent studies of deep learning and reinforcement learning for intelligent transportation
- Focuses on popular topics including processing traffic data, transportation network representation, traffic flow forecasting, traffic signal control, automatic vehicle detection, traffic incident processing, travel demand prediction, and autonomous driving and driver behaviors
- Provides new insights on how Big Data and Deep Learning can be used to build intelligent transportation systems to achieve safety and optimize performance and economy
- Thanks for edits in advance
Part of the book series: Studies in Computational Intelligence (SCI, volume 945)
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Table of contents (12 chapters)
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Front Matter
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Big Data and Autonomous Vehicles
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Front Matter
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Deep Learning and Object Detection for Safe Driving
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Front Matter
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AI and IoT for Intelligent Transportation
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Front Matter
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Keywords
About this book
This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today’s technology. Road sensors, UAVs, GPS, CCTV and incident reports are sources of massive amount of data which are crucial to make serious traffic decisions. Herewith this substantial volume and velocity of data, it is challenging to build reliable prediction models based on machine learning methods and traditional relational database. Therefore, this book includes recent research works on big data, deep convolution networks and IoT-based smart solutions to limit the vehicle’s speed in a particular region, to support autonomous safe driving and to detect animals on roads for mitigating animal-vehicle accidents. This book serves broad readers including researchers, academicians, students and working professional in vehicles manufacturing, health and transportation departments and networking companies.
Editors and Affiliations
Bibliographic Information
Book Title: Deep Learning and Big Data for Intelligent Transportation
Book Subtitle: Enabling Technologies and Future Trends
Editors: Khaled R. Ahmed, Aboul Ella Hassanien
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-65661-4
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-65660-7Published: 11 April 2021
Softcover ISBN: 978-3-030-65663-8Published: 12 April 2022
eBook ISBN: 978-3-030-65661-4Published: 10 April 2021
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: X, 264
Number of Illustrations: 28 b/w illustrations, 102 illustrations in colour
Topics: Data Engineering, Transportation Technology and Traffic Engineering, Computational Intelligence