The study presents empirical observations and simulations of congested traffic states on German freeways, focusing on how traffic behaves near road inhomogeneities such as lane closings, intersections, and uphill gradients. The research uses a novel microscopic model called the "intelligent driver model" (IDM) to simulate traffic dynamics. The IDM model is based on empirical boundary conditions and captures various traffic states, including localized and extended congestion, oscillating traffic, and coexisting states. The findings are consistent with a theoretical phase diagram for traffic near on-ramps, which describes different traffic states based on inflow and bottleneck strength. The IDM model is shown to reproduce these states by varying a single parameter, the average time headway. The model also demonstrates the existence of metastable and unstable traffic states, and it can simulate traffic breakdowns with empirical boundary conditions. The study highlights the importance of understanding traffic dynamics in open systems and provides insights into the behavior of traffic under different conditions. The results suggest that the phase diagram is a universal framework for traffic models and can be applied to various scenarios. The study also includes empirical data from different freeways, showing the occurrence of various traffic states and their characteristics. The findings support the use of the IDM model for simulating real-world traffic scenarios and provide a basis for further research into traffic dynamics.The study presents empirical observations and simulations of congested traffic states on German freeways, focusing on how traffic behaves near road inhomogeneities such as lane closings, intersections, and uphill gradients. The research uses a novel microscopic model called the "intelligent driver model" (IDM) to simulate traffic dynamics. The IDM model is based on empirical boundary conditions and captures various traffic states, including localized and extended congestion, oscillating traffic, and coexisting states. The findings are consistent with a theoretical phase diagram for traffic near on-ramps, which describes different traffic states based on inflow and bottleneck strength. The IDM model is shown to reproduce these states by varying a single parameter, the average time headway. The model also demonstrates the existence of metastable and unstable traffic states, and it can simulate traffic breakdowns with empirical boundary conditions. The study highlights the importance of understanding traffic dynamics in open systems and provides insights into the behavior of traffic under different conditions. The results suggest that the phase diagram is a universal framework for traffic models and can be applied to various scenarios. The study also includes empirical data from different freeways, showing the occurrence of various traffic states and their characteristics. The findings support the use of the IDM model for simulating real-world traffic scenarios and provide a basis for further research into traffic dynamics.