Ridesharing and fleet sizing for On-Demand Multimodal Transit Systems

This paper considers the design of On-Demand Multimodal Transit Systems (ODMTS) that combine fixed bus/rail routes between transit hubs with on-demand shuttles serve first/last miles to/from hubs. The problem aims at finding a network for to allow set riders travel from their origins destinations, while minimizing sum costs, bus operating and rider times. addresses two gaps in existing tools designing ODMTS. First, it generalizes prior work by including ridesharing shuttle rides. Second, proposes novel fleet-sizing algorithms determining number needed meet performance metrics ODMTS design. Both contributions are based on Mixed-Integer Programs (MIP). For design, MIP reasons about pickup dropoff order capture ridesharing, grouping who same hub. optimization is modeled as minimum flow covering constraints. natural formulation leads dense graph computational issues, which addressed reformulation works sparse graph. methodological evaluated real case study: public system broader Ann Arbor Ypsilanti region Michigan. results demonstrate substantial potential ODMTS, costs reduced 26% respect allowing only individual rides, expense minimal increase Compared system, designed also cuts down 35% reduces times 38%.