MiRoVA – Migration of Road Vehicle Automation

Project period: 02/2025 – 02/2029

Technical advancements in driver assistance and automation systems have progressed to the point where high levels of vehicle automation, up to and including fully automated driving, appear possible. In simplified terms, this involves replacing the human driver in the control process with a technical subsystem, a driving robot, with which the user can still communicate. The public sometimes gets the impression that this development is happening very quickly, almost overnight, and will extend to all areas of transportation. However, the actual deployment of fully autonomous driving systems "anytime, anywhere" is not yet feasible in the near future. It is much more likely that there will be a gradual development from partially to highly to fully automated and ultimately autonomous systems, in which concepts, technical subsystems, and users alike will evolve through various stages over time. A linear, highly simplified representation is provided by so-called roadmaps, such as those described by the VDA (Bartels & Ruchatz, 2015) based on research-supported working groups of the BASt (e.g., Gasser et al., 2012). This transition is referred to below as the migration of automation levels. The endpoint need not necessarily be a fully automated system; it can also be a system that strikes a good balance between automation and human freedom, offering varying degrees of assistance and automation.

Project goal

In this context, the MiRoVA project focuses on the automation process and the migration paths of vehicles. This includes not only the microscopic migration between vehicle automation and drivers, other road users, and technical systems, but also the macroscopic perspective on the changes in the transport system. This includes, for example, the integration of automated vehicles into existing traffic, in particular how such vehicles can be integrated into traffic with non-automated or low-level automated vehicles and other road users such as pedestrians or cyclists without causing cooperation problems. The overarching goal of this project is to identify the effects of current and future migration of human-technology interactions in automated transport systems on the safety and efficiency of road traffic, as well as on usability and acceptance (including user experience). A contribution to the research question of human-technology migration is the question of research methods: How can and should the migration effects be scientifically investigated?

The research group's basic approach is illustrated in the following figure. Starting with the fundamental research question, TP1 compiles knowledge about migration and migration effects in a metamodel. Based on this metamodel, TP2 investigates the migration of external interaction between vulnerable road users and automated vehicles. TP3 investigates the migration of automation itself. TP4 examines the migration of internal interaction and HMI, and TP5 investigates the migration of interaction between multiple vehicles. TP6 integrates a subset of the models from TP1-5 into a traffic simulation and examines the migration effects on traffic flow and tactical behavior. TP7 explores how research on migration effects can be supported by a virtual laboratory.

The LfE (Leibniz Institute for Environmental, Safety, and Energy Technology) is primarily involved in TP 5 (Technical Project 5) "Multiple People and Automation: Modeling Heterogeneously Automated Road Users and Their Cooperation." This research project will be completed in four years, with the LfE primarily investigating and modeling the cooperation between multiple heterogeneously automated road users. The research explores whether and how the cooperation and migration capabilities of these road users can be specifically influenced. The goal is to gain a deeper understanding of the processes in mixed traffic, examine potential incentive systems, and evaluate them using models. This will involve identifying incentives that could lead to both positive and negative outcomes in cooperation during migration.