It is a great pleasure to announce that on Monday, June 24, my mentee Viktor Lizenberg successfully defended his PhD thesis at Carl von Ossietzky University Oldenburg, under the academic supervision by Prof. Frank Köster of German Aerospace Center Institute for Safety and Security of Artificial Intelligence. His work was focused on new agent-based simulative methods for the development and validation of cooperative driving. He introduced a special Prototype-in-the-Loop method where a real vehicle is driving on a real proving ground in virtual traffic created from a co-simulation of surround traffic by manipulation of a real sensor channel, V2X.
A good overview of his work is found in this paper prepared for the SAE World Congress 2021 in Detroit, which was recommended by session chairs of SAE conferences as one of their best papers for journal publication in "SAE International Journal of Advances and Current Practices in Mobility"
"Cooperative Maneuver Coordination is one of the cornerstone technologies on the way to automated and connected driving of the future. The goal of this technology is to increase traffic safety and efficiency, by solving potential conflict situations on the road, based on cooperative maneuver planning, negotiation and decision-making, with the aid of inter-vehicular communication. This innovative topic represents a wide area for research projects, e.g., such as German funded project IMAGinE. A variety of different approaches for CMC has already been implemented and evaluated in the related work of the recent past. However, due to the high system complexity in general and vast testing effort in particular of these solutions, their actual impact on the traffic quality has not yet been extensively addressed, and therefore must be further investigated. In order to fulfill this task, one needs a methodology with appropriate evaluation metrics alongside with a suitable testing environment, in order to obtain comprehensive results. The scientific contribution of the work at hand involves a simulation-based evaluation methodology for CMC. For this, we will propose a novel CMC algorithm, which is built upon a direct trajectory exchange via inter-vehicular communication and a decentralized decision-making process, suitable for both manually operated as well as autonomous vehicles. In order to examine this algorithm, we will introduce a co-simulation environment with automatic scenario generation and multi-instances capability, which consists of a coupled simulation of traffic flow and vehicle dynamics. Eventually, we will present a set of metrics, which we determined in order to evaluate effectiveness and efficiency of our CMC algorithm, considering its impact on various aspects of the traffic quality."