From Effects to Causes: Reversible Simulation and Reverse Exploration of Microscopic Traffic Models

We propose an approach for reverse-in-time exploration of the state space of microscopic traffic simulations starting from a user-specified class of outcomes. As a basis for our approach, we present a reversible execution scheme applicable to common car-following and lane-changing models from the traffic simulation literature. The execution scheme permits perfect reversal of a previous forward simulation, which to our knowledge has not been attempted previously in the context of established traffic simulation models. Further, we perform reverse state space explorations directly from user-specified simulation states, i.e., reverse-in-time model checking. By exploring all sequences of possible previous states from a final state, reachability questions can be answered more conclusively than purely through forward simulations. In a case study, reverse exploration is used to identify conditions that lead to specified accident situations, with running time reductions by factors of more than 20 compared to traditional forward exploration.