MITNAND

Participatory Mobility Innovations Through Networked and Adaptive Traffic Infrastructure Design

Principal Investigators 

Prof. Klaus Bogenberger,
Chair of Traffic Engineering and Control, TUM School of Engineering and Design

Prof. Alois Knoll, 
Chair of Robotics, Artificial Intelligence and Real-Time Systems, TUM School of Computation, Information and Technology

Abstract The automation of road traffic will profoundly reshape cities by improving efficiency and safety while reducing the space needed for vehicles. This creates opportunities to repurpose urban areas for pedestrians, cyclists, and green spaces, enhancing livability and sustainability. However, these types of transformation demand advanced tools for engineers and urban planners to address the complex interactions between automated vehicles, bicycles, and pedestrians. This research develops an interactive AI-driven framework enabling practitioners to engage citizens directly in urban design and mobility planning. By combining established transportation engineering methods with rapid response AI models, the project creates a quasi-real-time digital twin of the urban environment. This digital twin dynamically visualizes current conditions and alternative infrastructure or control strategies through an adaptive 3D city model. The system enables practitioners and citizens to collaboratively explore design interventions, assess their traffic impact, and intuitively understand their consequences. The outcome is a participatory platform that links automated traffic, human mobility, and urban design, bridging technical modeling with public involvement to support transparent, data-driven decisions for future cities.