This study provides a large-scale micro-simulation of transportation patterns in a
metropolitan area when relying on a system of shared autonomous vehicles (SAVs). The
six-county region of Austin, Texas is used for its land development patterns, demographics,
networks, and trip tables. The agent-based MATSim toolkit allows modelers to
track individual travelers and individual vehicles, with great temporal and spatial detail.
MATSim’s algorithms help improve individual travel plans (by changing tour and trip start
times, destinations, modes, and routes). Here, the SAV mode requests were simulated
through a stochastic process for four possible fare levels: $0.50, $0.75, $1, and $1.25 per
trip-mile. These fares resulted in mode splits of 50.9, 12.9, 10.5, and 9.2% of the region’s
person-trips, respectively. Mode choice results show longer-distance travelers preferring
SAVs to private, human-driven vehicles (HVs)—thanks to the reduced burden of SAV
travel (since one does not have to drive the vehicle). For travelers whose households do not
own an HV, SAVs (rather than transit, walking and biking) appear preferable for trips

• Tracking a system of shared autonomous vehicles across the Austin, Texas network using agent-based simulation