Cooperatively Interacting Vehicles

Christoph Stiller studied Electrical Engineering at Aachen University, Germany, receiving his Diploma and Dr.-Ing. degree in 1988 and 1994. He was Postdoc at INRS in Montreal, Canada, before joining Robert Bosch GmbH. In 2001, he became Professor at Karlsruhe Institute of Technology. He has undertaken sabbaticals at CSIRO in Brisbane, Australia, Bosch RTC/Stanford University, and University of California Berkeley. He is IEEE Fellow, has held editorial positions for several IEEE Journals and served as President of the IEEE Intelligent Transportation Systems Society.

Matthias Althoff received the diploma in Mechatronics and Information Technology and the PhD degree from Technische Universität München, TUM, in 2005 and 2010. From 2010 - 2012 he was a postdoctoral researcher at Carnegie Mellon University, USA. In 2012, he joined Ilmenau University, Germany and TUM in 2013 as assistant and since 2019 as associate professor. His research interests include the design and analysis of cyber-physical systems, formal verification of continuous and hybrid systems, reachability analysis, planning algorithms, robust control, and safe machine learning. Main applications of his research are automated vehicles, robotics, power systems, and analog and mixed-signal circuits.

Christoph Burger received his B.Sc. and M.Sc. degree in mechanical engineering from Karlsruhe Institute of Technology (KIT) in Germany. He conducted his doctoral research at KIT, focusing on the research of cooperative, interaction-aware motion planning for automated vehicles. In 2022, he received his Dr.-Ing. degree (Ph.D.).

Barbara Deml studied psychology at the University of Regensburg, Germany, and received her doctorate in engineering from the University of the Federal Armed Forces in 2004. After post-doctoral work she was appointed to a junior professorship in Cognitive Ergonomics. In 2009, she followed a call to Otto-von-Guericke University Magdeburg to head the Chair of Ergonomics. Since 2012, Barbara Deml has headed the Institute of Human and Industrial Engineering at the Karlsruhe Institute of Technology. Her research focuses on the design of new work systems, such as robot cars.

Lutz Eckstein studied Mechanical Engineering and received the Diploma and Dr.-Ing. degree (Ph.D.) from Stuttgart University, Germany, in 1995 and 2000. After four years of research at Daimler-Benz AG, he was responsible for Active Safety of ADAS. In 2005 he was appointed senior manager HMI & Ergonomics at BMW AG. In 2010, he became Chaired Professor at Aachen University for Automotive Engineering.  Since 2023, he serves as President of the association of German engineers, VDI. He is member of the Scientific Advisory Board of the German Government and coordinator of the large scale project UNICARagil.

Frank Ole Flemisch started as aerospace engineer with a specialization in systems engineering and system dynamics. He did research on assistant systems and automation at University of Munich, NASA and DLR, served as the lead of a national standardization group and a technical expert in ISO TC204. He was involved in coining the terms highly automated driving and cooperative automation. Since 2011 he is leading a department of Human System Integration at the Fraunhofer FKIE, is Professor for Human Systems Integration at the Aachen University, and member of the NATO-STO Human Factors and Medicine Panel. In 2024, he was appointed principal scientist and Human Systems Evangelist of Fraunhofer FKIE.

This open access book explores the recent developments automated driving and Car2x-communications are opening up attractive opportunities future mobility. The DFG priority program "Cooperatively Interacting Automobiles" has focused on the scientific foundations for communication-based automated cooperativity in traffic.  

Communication among traffic participants allows for safe and convenient traffic that will emerge in swarm like flow. This book investigates requirements for a cooperative transport system, motion generation that is safe and effective and yields social acceptance by all road users, as well as appropriate system architectures and robust cooperative cognition.

For many years, traffic will not be fully automated, but automated vehicles share their space with manually driven vehicles, two-wheelers, pedestrians, and others. Such a mixed traffic scenario exhibits numerous facets of potential cooperation.  Automated vehicles mustunderstand basic principles of human interaction in traffic situations. Methods for the anticipation of human movement as well as methods for generating behavior that can be anticipated by others are required. Explicit maneuver coordination among automated vehicles using Car2X-communications allows generation of safe trajectories within milliseconds, even in safety-critical situations, in which drivers are unable to communicate and react, whereas today's vehicles delete their information after passing through a situation, cooperatively interacting automobiles should aggregate their knowledge in a collective data and information base and make it available to subsequent traffic.

Part I. Perception and Prediction with Implicit Communication.- Chapter 1. How cyclists' body posture can support a cooperative interaction in automated driving (Daniel Trommler).- Chapter 2. Prediction of cyclists' interaction-aware trajectory for cooperative automated vehicles (Dominik Raeck).- Chapter 3. Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence as a Basis for Automated Driving (DeCoInt2) (Stefan Zernetsch).- Chapter 4. Analysis and simulation of driving behavior at inner city intersections (Hannes Weinreuter).- Part II. Perception and Prediction with Explicit Communication.- Chapter 5. Robust Local and Cooperative Perception under Varying Weather Conditions (Jörg Gamerdinger).- Chapter 6. Design and Evaluation of V2X Communication Protocols for Cooperatively Interacting Automobiles (Quentin Delooz).- Part III. Motion Planning.- Chapter 7. Interaction-Aware Motion Planning as a Game (Christoph Burger).- Chapter 8. Designing Maneuver Automata of Motion Primitives for Optimal Cooperative Trajectory Planning (Matheus V. A. Pedrosa).- Chapter 9. Prioritized Trajectory Planning for Networked Vehicles Using Motion Primitives (Patrick Scheffe).- Chapter 10. Maneuver-level cooperation of automated vehicles (Matthias Nichting).- Chapter 11. Hierarchical Motion Planning for Consistent and Safe Decisions in Cooperative Autonomous Driving (Jan Eilbrecht).- Chapter 12. Specification-Compliant Motion Planning of Cooperative Vehicles Using Reachable Set (Edmond Irani Liu).- Chapter 13. AutoKnigge - Modeling, Evaluation and Verification of Cooperative Interacting Automobiles (Christian Kehl).- Chapter 14. Implicit Cooperative Trajectory Planning under Uncertainty with Learned Rewards (Karl Kurzer).- Chapter 15. Learning Cooperative Trajectories at Intersections in Mixed Traffic via Reinforcement Learning (S. Yan).- Part IV. Human Factors.- Chapter 16. Cooperative Hub for Cooperative Research on Cooperatively Interacting Vehicles: Use-Cases, Design and Interaction Patterns (Frank Flemisch).- Chapter 17. Cooperation between Vehicle and Driver: Predicting the Driver's Takeover Capability in Cooperative Automated Driving based on Orientation Patterns (Nicolas Herzberger).- Chapter 18. Confidence Horizons: Dynamic Balance of Human and Automation Control Ability in Cooperative Automated Driving (Marcel Usai).- Chapter 19. Cooperation Behavior of Drivers at Inner City Deadlock-Situations (Nadine-Rebecca Strelau).- Chapter 20. Measuring and describing cooperation between road users - Results from CoMove (Laura Quante).