Hybrid Multimodal and Intermodal Transport Simulation: Case Study on Large-Scale Evacuation Planning

Transport simulation models exist on multiple scales, from the simulated evacuation of a nightclub with a few hundred guests to that of a transport hub such as a large train station to the simulated evacuation of a megalopolis in case of a tsunami. Depending on precision and complexity requirements, continuous (e.g., force-based, velocity obstacle–based), spatiotemporal discrete (e.g., cellular automata), or queue models are applied. In general, the finer the spatiotemporal resolution, the more precise are the interactions captured between travelers (e.g., pedestrians or vehicles), but the computational burden increases. The obvious approach to achieve higher computational speeds is to reduce the physical complexity (e.g., by using a queue model), which in turn reduces the precision. One way to increase the computational speed while retaining sufficient precision to make a reliable prognosis is to combine models of different scale in a hybrid manner, in which a finer model is applied where needed and a coarser model where plausible. This paper discusses an application of a hybrid simulation approach in the context of a large-scale multimodal and intermodal evacuation scenario. The presented case study investigates the feasibility of an evacuation of parts of the city of Hamburg, Germany, in case of a storm surge