Smart Transportation
AI Enabled Mobility and Autonomous Driving
Herausgeber: Dartmann, Guido; Lücken, Volker; Schmeink, Anke
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Smart Transportation
AI Enabled Mobility and Autonomous Driving
Herausgeber: Dartmann, Guido; Lücken, Volker; Schmeink, Anke
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This book presents a review of the progress and latest applications of artificial intelligence in autonomous vehicles and its implementation in new hardware platforms. Furthermore, new concepts for mobility services based on this technology are presented and the social and human factors are discussed.
This book presents a review of the progress and latest applications of artificial intelligence in autonomous vehicles and its implementation in new hardware platforms. Furthermore, new concepts for mobility services based on this technology are presented and the social and human factors are discussed.
Produktdetails
- Produktdetails
- Verlag: Taylor and Francis
- Seitenzahl: 256
- Erscheinungstermin: 11. November 2021
- Englisch
- Abmessung: 234mm x 156mm x 16mm
- Gewicht: 535g
- ISBN-13: 9780367352967
- ISBN-10: 0367352966
- Artikelnr.: 62224225
- Verlag: Taylor and Francis
- Seitenzahl: 256
- Erscheinungstermin: 11. November 2021
- Englisch
- Abmessung: 234mm x 156mm x 16mm
- Gewicht: 535g
- ISBN-13: 9780367352967
- ISBN-10: 0367352966
- Artikelnr.: 62224225
Guido Dartmann is Professor and Group Leader of the research area Distributed Systems and member of the Institute for Software Systems at the Environmental Campus, Trier University of Applied Sciences, Trier, Germany. Guido Dartmann studied Computer Engineering at the RWTH Aachen University and received the Dipl.-Ing. in 2007. After his graduate studies, he became research assistant at the Institute of Communication Technology and Embedded Systems (ICE) of the RWTH Aachen University where he finished his PhD and received the Borchers Medal of the RWTH Aachen. In 2012, he became chief engineer at ICE. Since 02/2016, Prof. Dartmann is a full professor at Trier University of Applied Sciences. His research interests include distributed systems, machine learning, data analytics, signal processing, optimization of technical systems, cyber-physical systems, wireless communication, cyber-security, internet of things, traffic and mobility. His research group at the Environmental Campus was granted by several grants of German federal ministries and European research. Prof. Dartmann is senior member of the IEEE and reviewer of several IEEE Transactions and he and he is co-author of more than 80 scientific papers in peer-reviewed journals, books and conference proceedings. Prof. Dartmann is co-lead and member of the expert group Internet of Things at the national Information Technology Summit. Anke Schmeink is Professor and Leader of the research area Information Theory and Systematic Design of Communication Systems (ISEK) at RWTH Aachen University, Aachen, Germany. Anke Schmeink received the diploma degree in mathematics with a minor in medicine and the Ph.D. degree in electrical engineering and information technology from RWTH Aachen. She worked as a research scientist for Philips Research and is a professor at RWTH Aachen since 2012. Anke Schmeink is a senior member of IEEE, an editor for IEEE TWC and founding member of the IEEE Special Interest Group on Big Data Intelligent Network. She spent several research visits with the University of Melbourne, Australia, and with the University of York, UK. She has received diverse awards, in particular, three best paper awards and the Vodafone Young Scientist Award. Anke Schmeink has been reviewer for several journal papers and conference proceedings and has been on the technical program committee for numerous international conferences. Anke Schmeink has published more than 160 scientific papers in peer-reviewed journals and conference proceedings. Her research interests are in information theory and machine learning, the optimization of networks and biomedical problems and the analysis of the resulting data. Volker Lücken is the Competence Center Lead for Connectivity & IoT and Senior Manager at umlaut, Aachen, Germany. Previously he has been working as the Teamleader Strategic Research as well as an Expert for Autonomous Driving at e.GO Mobile AG, Aachen, Germany. Volker Lücken received his diploma degree in electrical engineering from RWTH Aachen University, with a focus on information and communication technology. From 2012 to 2018, he worked as a research associate at the Institute for Communication Technologies and Embedded Systems (ICE), RWTH Aachen University. There, his fields of interest were mobile communications, embedded systems, signal processing and machine learning applications. Besides several publications and patents in these fields, he also accompanied the research & development and commercialization for Smart-City-centric IoT and sensor signal processing applications. For his work, he also received the "HiPEAC Technology Transfer Award" in 2017. In 2018, he joined the research department of e.GO Mobile AG, which is an automotive OEM in the field of electrical mobility. There, he covers the topics of automated driving technologies and artificial intelligence applications, and is responsible for several research projects in these domains. Houbing Song is the Director of the Security and Optimization for Networked Globe Laboratory (SONG Lab, http://songlab.us/), and an Assistant Professor of Electrical Engineering and Computer Science, Embry-Riddle Aeronautical University, Daytona Beach, Florida, USA. He received the Ph.D. degree in electrical engineering from the University of Virginia, Charlottesville, VA, in August 2012, and the M.S. degree in civil engineering from the University of Texas, El Paso, TX, in December 2006. In August 2017, he joined the Department of Electrical Engineering and Computer Science, Embry-Riddle Aeronautical University, Daytona Beach, FL, where he is currently an Assistant Professor and the Director of the Security and Optimization for Networked Globe Laboratory (SONG Lab, www.SONGLab.us). He has served as an Associate Technical Editor for IEEE Communications Magazine (2017-present), an Associate Editor for IEEE Internet of Things Journal (2020-present) and IEEE Journal on Miniaturization for Air and Space Systems (J-MASS) (2020-present). He is the editor of six books and the author of more than 100 articles. His research interests include cyber-physical systems, cybersecurity and privacy, internet of things, edge computing, AI/machine learning, big data analytics, unmanned aircraft systems. His research has been featured by popular news media outlets, including IEEE GlobalSpec's Engineering360, Association for Unmanned Vehicle Systems International (AUVSI), Fox News, USA Today, U.S. News & World Report, Forbes, The Washington Times, WFTV, and New Atlas. Dr. Song is a senior member of ACM and an ACM Distinguished Speaker. Dr. Song was a recipient of the Best Paper Awards from CPSCom-2019, ICII 2019, ICNS 2019, CBDCom 2020, and WASA 2020. Martina Ziefle is a full professor and leads the chair of Communication Science at RWTH Aachen University. She is one of four directors of the Human-Computer Interaction Center (HCIC) at RWTH Aachen, Germany. She is a psychologist by education. Her research is concerned with human interaction and communication of humans with technology addressing the human factor in different technology types and using contexts. The impact of individual cognitive and affective factors on technology acceptance and the interaction and communication between humans and technology is integral part of the user-centered research approach. A special research focus is directed to humans and their interaction and communication with autonomous vehicles, exploring users' perceptions, attitudes and social factors that influence the intention to use novel mobility technologies. Martina Ziefle is (co-)author of more than 400 publications (h-index 43, as taken from google scholar). Martina Ziefle leads various projects funded by industry and public authorities, dealing with technology acceptance, risk perception and communication as well as the interaction and communication of humans with technology. Giovanni Prestifilippo has been Managing Director of PSI Logistics since 2013, where he had been Group Director and Board Member at the Dortmund location since 2008. With a doctorate in IT, he has directed and shaped the development and marketing of the PSIglobal product from the start. He previously held a management position from 1993 at the Fraunhofer Institute for Material Flow and Logistics (IML), and completed a doctorate in the Mechanical Engineering faculty of Dortmund University on efficient algorithms in logistics. Until 2009, he acted both as a Partner and Senior Partner in VCE Verkehrslogistik GmbH. With a background of many years of experience in analysis, planning and optimisation of complex logistics networks, since 2001 he has also been a speaker and lecturer on logistics subjects. Dr. Giovanni Prestifilippo is associated with various research institutions such as the RWTH, TU Berlin, TU Dortmund, several Fraunhofer Institutes such as IML, IPK, FIT as well as the BVL, VDI, VDMA and GOR.
1. Social Acceptance of Autonomous Driving - The Importance of Public
Discourse and Citizen Participation 2. Artificial Intelligence for
Autonomous Vehicle Fleets: Desired Requirements, Solutions and a Best
Practice Project 3. Large-scale Simulation of a Mobility-on-Demand System
for the German City Aachen 4. Artificial Intelligence for Fleets of
Autonomous Vehicles: Desired Requirements and Solution Approaches 5. Future
Urban Mobility: Designing New Mobility Technologies in Open Innovation
Networks 6. Communication and Service Aspects of Smart Mobility: Improving
Security, Privacy and Efficiency of Mobility Services by Utilizing
Distributed Ledger Technology 7. Pseudonym Management through Blockchain:
Cost-efficient Privacy Preservation on Smart Transportation 8. Simulation
Platforms for Autonomous Driving and Smart Mobility: Simulation Platforms,
Concepts, Software, APIs 9. Deep-Learning Based Depth Completion for
Autonomous Driving Applications 10. Artificial Intelligence Based on
Modular Reinforcement Learning and Unsupervised Learning 11. Functional
Safety of Deep Learning Techniques in Autonomous Driving Systems
Discourse and Citizen Participation 2. Artificial Intelligence for
Autonomous Vehicle Fleets: Desired Requirements, Solutions and a Best
Practice Project 3. Large-scale Simulation of a Mobility-on-Demand System
for the German City Aachen 4. Artificial Intelligence for Fleets of
Autonomous Vehicles: Desired Requirements and Solution Approaches 5. Future
Urban Mobility: Designing New Mobility Technologies in Open Innovation
Networks 6. Communication and Service Aspects of Smart Mobility: Improving
Security, Privacy and Efficiency of Mobility Services by Utilizing
Distributed Ledger Technology 7. Pseudonym Management through Blockchain:
Cost-efficient Privacy Preservation on Smart Transportation 8. Simulation
Platforms for Autonomous Driving and Smart Mobility: Simulation Platforms,
Concepts, Software, APIs 9. Deep-Learning Based Depth Completion for
Autonomous Driving Applications 10. Artificial Intelligence Based on
Modular Reinforcement Learning and Unsupervised Learning 11. Functional
Safety of Deep Learning Techniques in Autonomous Driving Systems
1. Social Acceptance of Autonomous Driving - The Importance of Public
Discourse and Citizen Participation 2. Artificial Intelligence for
Autonomous Vehicle Fleets: Desired Requirements, Solutions and a Best
Practice Project 3. Large-scale Simulation of a Mobility-on-Demand System
for the German City Aachen 4. Artificial Intelligence for Fleets of
Autonomous Vehicles: Desired Requirements and Solution Approaches 5. Future
Urban Mobility: Designing New Mobility Technologies in Open Innovation
Networks 6. Communication and Service Aspects of Smart Mobility: Improving
Security, Privacy and Efficiency of Mobility Services by Utilizing
Distributed Ledger Technology 7. Pseudonym Management through Blockchain:
Cost-efficient Privacy Preservation on Smart Transportation 8. Simulation
Platforms for Autonomous Driving and Smart Mobility: Simulation Platforms,
Concepts, Software, APIs 9. Deep-Learning Based Depth Completion for
Autonomous Driving Applications 10. Artificial Intelligence Based on
Modular Reinforcement Learning and Unsupervised Learning 11. Functional
Safety of Deep Learning Techniques in Autonomous Driving Systems
Discourse and Citizen Participation 2. Artificial Intelligence for
Autonomous Vehicle Fleets: Desired Requirements, Solutions and a Best
Practice Project 3. Large-scale Simulation of a Mobility-on-Demand System
for the German City Aachen 4. Artificial Intelligence for Fleets of
Autonomous Vehicles: Desired Requirements and Solution Approaches 5. Future
Urban Mobility: Designing New Mobility Technologies in Open Innovation
Networks 6. Communication and Service Aspects of Smart Mobility: Improving
Security, Privacy and Efficiency of Mobility Services by Utilizing
Distributed Ledger Technology 7. Pseudonym Management through Blockchain:
Cost-efficient Privacy Preservation on Smart Transportation 8. Simulation
Platforms for Autonomous Driving and Smart Mobility: Simulation Platforms,
Concepts, Software, APIs 9. Deep-Learning Based Depth Completion for
Autonomous Driving Applications 10. Artificial Intelligence Based on
Modular Reinforcement Learning and Unsupervised Learning 11. Functional
Safety of Deep Learning Techniques in Autonomous Driving Systems