Traffic twins
Traffic Management and Simulation Tool for decision-making: TULIPE project
Urban traffic management struggles to evaluate and mitigate the impact of disruptive events like road closures on traffic flow. As part of the TULIPE project, an interactive tool was implemented to help traffic management experts define, compare, and assess road deviation plans using different traffic models. Evaluation with a synthetic traffic model demonstrates the tool’s usefulness in supporting decision-making for transportation infrastructure management.
Advancing Traffic Management: Digital Twin Model for Smarter Intersection Design and Optimization
Managing traffic at intersections is challenging, requiring accurate predictions and real-time decision-making. This demo shows a digital twin of a traffic intersection, integrating real-time data and machine learning to predict traffic conditions and serve as a reliable reference model. The digital twin enables proactive congestion management and provides a safe environment to test traffic control strategies before real-world implementation.
Simulating Traffic Networks: Driving SUMO towards digital twins
Urban spaces are increasingly dominated by cars, leading to environmental pollution and inefficient land use, while alternative mobility options remain unattractive to many. This demo presents the development of a digital twin in SUMO, integrating static and dynamic city data to simulate and analyze intermodal mobility networks. Using Osnabrück as a case study, the demo explores data availability, integration challenges, and future improvements for better urban mobility planning.
Traffic prOcessing foR uRban EnvironmentS (TORRES) 