  This study addresses a large-scale multimodal transit network design problem,
with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an
origin-to-destination mode. The framework captures spatial demand and modal
characteristics, considers intermodal transfers and express services,
determines transit infrastructure investment and path flows, and generates
transit routes. A system-optimal multimodal transit network is designed with
minimum total door-to-door generalized costs of users and operators, satisfying
transit origin-destination demand within a pre-set infrastructure budget.
Firstly, the geography, demand, and modes in each zone are characterized with
continuous approximation. The decisions of network link investment and
multimodal path flows in zonal connection optimization are formulated as a
minimum-cost multi-commodity network flow (MCNF) problem and solved efficiently
with a mixed-integer linear programming (MILP) solver. Subsequently, the route
generation problem is solved by expanding the MCNF formulation to minimize
intramodal transfers. The model is illustrated through a set of experiments
with the Chicago network comprised of 50 zones and seven modes, under three
scenarios. The computational results present savings in traveler journey time
and operator cost demonstrating the potential benefits of collaboration between
multimodal transit systems and SAMS.
