Towards Highly Interactive, GPU-based Evaluation of Evacuation Transport Scenarios at State-Scale

Abstract

In large-scale scenarios, transportation modeling and simulation is severely constrained by simulation time. For example, few real-time simulators exist that can scale to evacuation traffic scenarios at the level of an entire state such as Louisiana (approx. 1 million links) or Florida (2.5 million links). New modeling techniques are needed to overcome severe computational demands of conventional (microscopic or mesoscopic) modeling techniques. Here, a modeling and execution methodology is explored which holds potential to provide a tradeoff among the level of behavioral detail, the scale of transportation network, and real-time execution capabilities. A novel, field-based modeling technique, and its implementation on graphical processing units (GPUs) are presented, as a step forward in enabling large-network transportation modeling and simulation. Although additional research with input from domain experts is needed for refining and validating the models, the techniques reported here afford interactive experience at hitherto fore unimaginable scales of multi-million road segments. Illustrative experiments on a few state-scale networks are described based on our implementation of this approach in a software system called GARFIELD-EVAC.