  The integration of traditional fixed-route transit (FRT) and more flexible
microtransit has been touted as a means of improving mobility and access to
opportunity, increasing transit ridership, and promoting environmental
sustainability. To help evaluate integrated FRT and microtransit public transit
(PT) system (henceforth ``integrated fixed-flex PT system'') designs, we
propose a high-fidelity modeling framework that provides reliable estimates for
a wide range of (i) performance metrics and (ii) integrated fixed-flex PT
system designs. We formulate the mode choice equilibrium problem as a
fixed-point problem wherein microtransit demand is a function of microtransit
performance, and microtransit performance depends on microtransit demand. We
propose a detailed agent-based simulation modeling framework that includes (i)
a binary logit mode choice model (private auto vs. transit), (ii) a
supernetwork-based model and pathfinding algorithm for multi-modal transit path
choice where the supernetwork includes pedestrian, FRT, and microtransit
layers, (iii) a detailed mobility-on-demand fleet simulator called FleetPy to
model the supply-demand dynamics of the microtransit service. In this paper, we
illustrate the capabilities of the modeling framework by analyzing integrated
fixed-flex PT system designs that vary the following design parameters: FRT
frequencies and microtransit fleet size, service region structure, virtual stop
coverage, and operating hours. We include case studies in downtown San Diego
and Lemon Grove, California. The computational results show that the proposed
modeling framework converges to a mode choice equilibrium. Moreover, the
scenario results imply that introducing a new microtransit service decreases
FRT ridership and requires additional subsidies, but it significantly increases
job accessibility and slightly reduces total VMT.
