Kai Nagel, Martin Skutella
Theresa Ziemke (TU) and Leon Sering (TU until 03/21, ETH Zurich since 04/21)
01.01.2019 – 30.11.2023
This interdisciplinary project studies the intersection of network flows, algorithmic game theory, and traffic simulation and control. The goal is to gain a better structural understanding and, based upon this, provide efficient algorithmic methods to handle real-world traffic scenarios, e.g., in the context of evacuation planning. In this interdisciplinary collaboration between mathematicians and traffic engineers, we develop advanced flow over time models and packet routing models for dynamic user equilibria and mathematically analyzed. Solutions resulting from novel flow over time methods are empirically evaluated and integrated into the large-scale agent-based transport simulation tool MATSim.
Even though real-world traffic consists of non-splittable vehicles, continuous flows over time describe average traffic rates. One of our results show that, from a stochastic point of view, the discrete MATSim model can be interpreted as a realization of a random experiment where the average of the distribution is given by a dynamic user equilibrium in the flow over time model. To confirm the strong connection between the two models even further, we analyzed the discretization error by decreasing the time step and vehicle size within a packet model similar to MATSim and proved that the travel times and cumulative inflow rates of the packet model converges to the respective functions in the flow over time model. Furthermore, we show that the convergence result implies the existence of approximate equilibria in the competitive version of the packet routing model. This is of significant interest as exact equilibria, similar to almost all other competitive models, cannot be guaranteed in the multi-commodity setting.
In addition to that, we extended the flow over time model by several real-world traffic features, such as spillback, kinematic waves and time-varying capacities and transit times and proved the existence of dynamic user equilibria in this generalized model.
Illustration of flow dynamics in MATSim (left hand side) and flow over time model (right hand side). The numbers denote the capacities.
Picture reference: 
Travel times by departure time in MATSim and in a Nash flow over time for time step size 1, 1/2, 1/4 and 1/8 (from left to right) in a Braess network with three routes: top, middle, bottom.
Picture reference: 
Their are six players, indicated by different colors. The transit times are depicted beside the arcs and all arcs have a capacity of 1. The two main players, pursuer 1 going from o_P to d_P and evader 2 going from o_E to d_E, are the only players who can choose a path. The purpose of the remaining four players is to transfer the information between the main players. By giving the four long arcs priority in the merging, we obtain a matching pennies game between the pursuer and the evader, which does not possess a Nash equilibrium.
Picture reference: 
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