Embedded Automotive Systems
Future transportation will be based on smart, wirelessly connected, tightly interacting, highly automated or even completely autonomous vehicles and support infrastructure. Throughout the next decade autonomous cars in particular are even considered to be one of the 10 most disruptive technologies with revolutionary impact on life, society and economy. Today's Embedded Automotive Systems already drive about 90% of the innovation in the automotive sector, and the corresponding Electronic Control Units already account for about 40% of the total vehicle development expenses. These numbers will keep growing along with an increasing complexity of the involved distributed computing systems and the high expectations on next-generation vehicles. To tackle the various existing problems and upcoming challenges, the the EAS working group covers the holistic research area "Automotive Hardware/Software/Networks" with a special focus on computer architectures (multi-core processors), system software (operating systems), and vehicular networks (self-organizing wireless communication) with the goal to conduct basic and applied research for dependable and efficient transportation.
Staff member
Coordinator
Univ.-Prof. Dipl.-Inf. Univ. Dr.rer.nat. Marcel Carsten Baunach
Participant
Eng. Leandro Batista Ribeiro
MSc Maja Malenko
Eng. Renata Martins Gomes
Dipl.-Ing. BSc Fabian Mauroner

Selected Publications

2017
Conference/Workshop Article
Tobias Peter Scheipel, Fabian Mauroner and Marcel Carsten Baunach System-Aware Performance Monitoring Unit für die RISC-V-Architektur 2017 Betriebssysteme und Echtzeit
Other Article
Fabian Mauroner and Marcel Carsten Baunach StackMMU: Dynamic Stack Sharing for Embedded Systems
Renata Martins Gomes, Marcel Carsten Baunach, Leandro Batista Ribeiro, Maja Malenko and Fabian Mauroner A Co-Designed RTOS and MCU Concept for Dynamically Composed Embedded Systems
Tobias Peter Scheipel, Fabian Mauroner and Marcel Carsten Baunach System-Aware Performance Monitoring Unit for RISC-V Architectures
Fabian Mauroner and Marcel Carsten Baunach EventIRQ: An Event based and Priority aware IRQ handling for Multi-Tasking Environments
Fabian Mauroner, Maja Malenko and Marcel Carsten Baunach mosartMCU: An Operating System aware real-Time MCU
Renata Martins Gomes, Leandro Batista Ribeiro and Marcel Carsten Baunach MCSmartOS: A Dependable OS for Compositional Embedded Systems
Renata Martins Gomes, Marcel Carsten Baunach and Leandro Batista Ribeiro MCSmartOS: A Dependable OS for Compositional Embedded Systems
2016
Book Chapter
Marcel Carsten Baunach and Leandro Batista Ribeiro 14. Workshop Automotive Software EngineeringLecture Notes in Informatics (LNI)
Marcel Carsten Baunach and Maja Malenko Real-Time and Security Requirements for the Internet of Things Operating SystemsECHTZEIT 2016
Journal Article
Carlo Alberto Boano, Kay Uwe Römer, Roderick Bloem, Klaus Witrisal, Marcel Carsten Baunach and Martin Horn Dependability for the Internet of Things
Conference/Workshop Article
Marcel Carsten Baunach and Peter Brungs Einsatz von dynamisch rekonfigurierbaren FPGAs in Fahrzeugen Lecture Notes in Informatics (LNI)
Other Article
Marcel Carsten Baunach Compositional Embedded Systems Designfor Multi-Tasking and Multi-Core Environments
Marcel Carsten Baunach Operating Systems and Processor Architectures for a Dependable Internet of Things
2015
Conference/Workshop Article
Marcel Carsten Baunach, Renata Martins Gomes and Fabian Mauroner Collaborative Resource Management for Multi-Core AUTOSAR OS Betriebssysteme und Echtzeit 1-10
Other Article
Fabian Mauroner and Marcel Carsten Baunach Hardware assisted Real-Time Resource Management for Multi-Core MCU Architectures
2014
Conference/Workshop Article
Marcel Carsten Baunach Advanced Timestamping for pairwise Clock Drift Detection in Wireless Sensor/Actuator Networks 13. GI/ITG KuVS Fachgespräch "Drahtlose Sensornetze" 1-4
Marcel Carsten Baunach Handling Time and Reactivity for Synchronization and Clock Drift Calculation in Wireless Sensor/Actuator Networks International Conference on Sensor Networks 63-72