Traffic Flow Fundamentals

Lead: Lisa Kessler, Anna Takayasu

The core topics of the research group comprise the optimization of traffic efficiency on existing transport networks. This includes the collection and analysis of macroscopic and microscopic traffic parameters and the derivation of theoretical concepts for traffic flow. We deal with multimodal transportation networks, with a special focus on bicycles and motorized vehicles.

Our gained knowledge is the basis for novel methods for traffic management and control. The work takes into account current technical developments (e.g., in sensor technology, automation, and artificial intelligence) and aims to find practical solutions to improve traffic efficiency and safety.

Traffic Flow Theory and Modeling:

• Spatio-temporal multimodal traffic state estimation, reconstruction, and prediction
• Incident detection in networks and on road segments
• Macroscopic fundamental diagram
• Microscopic traffic modeling and simulation

Traffic Monitoring, Management, and Technology:

• Traffic information and quality
• AI-based congestion prediction and management
• Traffic observations using novel sensors such as aerial drones and moving/parking vehicles
• Traffic and environmental data collection and evaluation

Traffic Efficiency:

• Effects of infrastructure design on traffic flow and behavior
• Network resilience and robustness
• Evaluation methods in transport
• AI-based optimization of multimodal traffic network design and control
• Impact of the level of stress for active traffic modes

Traffic Safety:

• Test studies on bicycle, wheelchair, and e-scooter simulators using VR environments
• Controlled experiments on test beds
• Real-field experiments with sensor bicycles and vehicles