Arbeitsgruppe Verteilte Systeme

Call for Chapter:

Smart Transportation: AI Enabled Mobility and Autonomous Driving (CRC Press | Taylor & Francis)

Edited by: Guido Dartmann, Anke Schmeink, Martina Ziefle, Giovanni Prestiflippo, Volker Lücken, Houbing Song

• Chapter Proposal Submission by: July 1st, 2019
• Author Notification by: August 30th, 2019
• Full Chapter Submission by: September 30th, 2019
• Review Results Returned by: October 30th, 2019
• Final Chapter Submission by: November 30th, 2019
• Anticipated Publication Date: Beginning, 2020

Every day billions of people commute to work, do their shopping or other tasks. The goal of the book is the presentation of a holistic approach towards smart transportation. The book is dedicated to new cloud, machine learning and communication technologies for an fully automized transport considering the needs of citizens. This will lead to complete change of recent concepts transport.

This book will therefore provide a broad overview of challenges and recent developments in the field of smart mobility and transportation. This includes technical, algorithmic as well as social aspects of smart mobility and transportation. The book will start with new ideas for services and platforms for future mobility. Then new concepts of artificial intelligence and the implementation in new hardware architecture is discussed. In the context of artificial intelligence, new challenges of machine learning and for autonomous vehicles and fleets are investigated. Finally, the book concludes with human factors and social questions of future mobility concepts.

Possible Chapters (but not limited to) are:

1. Communication and Service Aspects of smart Mobility: Communication Standards, Infrastructure, Cloud-Systems, and new trends in Blockchain
2. Concepts of new autonomous cars: platforms, sensors, hardware, software
3. Simulation platforms for Artificial Intelligence in smart mobility: Simulation platforms, concepts, Software, APIs
4. Energy-efficient implementation and integration of artificial intelligence in autonomous driving
5. Sensor technology and algorithms: Multi sensor fusion, detection, estimation, tracking
6. Artificial Intelligence for individual cars: Sensor Fusion, Object detection, Semantic mapping, Segmentation, end-to-end processing
7. Artificial Intelligence based on Reinforcement Learning: Concept, new trends, LSTMs, Autoencoder, etc.
8. Artificial Intelligence for fleets of Vehicles: Global optimization, distributed learning
9. Functional safety of deep learning techniques in autonomous driving
10. Hardware platforms for AI: new architectures for optimized hardware for machine learning and real-time applications
11. New smart services and scenarios for smart mobility: Scenarios (logistics, transportation, etc.)
12. Human Factors in automated driving
13. Public perceptions of driverless cars
14. Ethical, social and political factors in autonomous driving
15. Risk, Trust and User diversity in autonomous driving