The mobility of the future is closely linked to the transformation of existing mobility systems. Connectivity, digitalization, and the intelligent use of data are creating new opportunities to better analyze, understand, and shape transportation processes. In this context, digital twins are becoming increasingly important, as they provide data-driven representations of real-world mobility and traffic dynamics, thereby creating a solid foundation for planning, control, and new applications.

As part of the LiDiMoVer project, the University of Wuppertal, in collaboration with LASE PeCo Systemtechnik GmbH and Ruhr West University of Applied Sciences, is developing a LiDAR-based digital twin to analyze mobility behavior. The goal is to make mobility data available—from collection to usable processing—in a way that enables traffic planning and mobility services to be designed in a more informed, targeted, and needs-based manner. To achieve this, data on mobility behavior is collected using a sensor network, processed using artificial intelligence and statistical modeling techniques, and consolidated into a virtual representation of real-world traffic conditions—the digital twin. A target-group-specific dashboard is provided for decision-makers to utilize the collected data. The system is being tested in the “Am Schornacker” industrial park in the city of Wesel.

Through the TMDT and the research group led by Prof. Dr. Matthias Rottmann, the University of Wuppertal contributes expertise particularly in the areas of digital transformation, data analysis, AI-supported evaluation, and mathematical modeling. The TMDT’s mission is to analyze new areas of application in the context of mobility analysis using digital twins in order to support advanced applications, such as those in the smart city sector. In addition, the TMDT focuses on developing implementation strategies to support municipalities in the use of digital twins.