The future of mobility includes electrified, automated, and interconnected transportation systems tailored to different regional needs while designed to improve mobility safety and efficiency. This transformation includes redesigned mobility spaces and holistic mobility concepts for high-density urban areas as well as novel approaches for reaching remote and potentially dangerous locations through the use of supervised teleoperated mobile robot teams (e.g. for infrastructure maintenance).
Researchers in Mobility@MSRM (new MIRMI) are particularly dedicated to the two greatest challenges of current mobility, automated and electric driving.
According to the motto “Future Transport Mobility: We research vehicles for future mobility under the best conditions and share our knowledge”, the research is divided into the sub fields of Vehicle Dynamics and Control Systems, Automated Driving, Vehicle Concepts, Electric Powertrain and Smart Mobility.
In addition to the intelligent chassis of the future, which offer the passengers of automated vehicles optimum comfort and are able to identify defective vehicles independently, the focus of this research group is on the control of automated vehicles at the limit of their driving dynamics, as shown in the ROBORACE project.
This working group researches the safety of automated vehicles and their cooperative behavior in road traffic as well as the interaction between vehicle and passengers. In addition, teleoperated driving is developed as a fall-back level of automation, in which an automated vehicle can be controlled remotely in situations that it cannot solve itself.
The Electric Powertrain Research Group investigates and optimizes the high-voltage battery, power electronics and the electric motor as well as the interaction of the components in the electric drive train with the goal to increase the range, efficiency and sustainability of electric vehicles, for example through AI-based battery analytics systems.
The focus of this research group is on the topic of mobility. Starting point is the collection, processing and analysis of mobility data in the context of fleet tests. The aim is to obtain a detailed picture of the mobility behavior of the end user. We apply this knowledge in different contexts, for example for predicting mobility demand or designing the charging infrastructure for electric vehicles.
Prof. Dr.-Ing. habil. Alois Knoll
Chair of Robotics, Artificial Intelligence and Real-time Systems
Mobility@MSRM (new MIRMI) Sector Leader