Arcology design combines urban planning and architecture with the mechanics of ecology. The physical design of an arcology would encompass the creation of a "hyperstructure" that delivers utility and transportation infrastructure in a highly integrated compact package. This thesis defines and describes a prototype simulation framework that would execute and evaluate intelligent demand-responsive multimodal mass transit schemes. Given a set of connected nodes serviced by different fleets of vehicles, a global optimizer attempts to generate a coordinated fleet schedule that meets various demand patterns. Factorial design of experiments and parametric analysis on the resulting simulated performance data of several simplified 1D and 2D scenarios help identify significant system design variables, including the number and size of the vehicle fleet, station configuration, transit network topology, and initial distribution of travel demand between station nodes. This tool explores the effectiveness of transit-oriented design paradigms supporting arcologies and other urban forms.