OPERATIONS OF A SHARED AUTONOMOUS VEHICLE FLEET FOR THE AUSTIN, TEXAS MARKET

The emergence of self-driving vehicles holds great promise for the future of transportation. While it will still be a number of years before fully self-driving vehicles can safely and legally drive unoccupied on U.S. street, once this is possible, a new transportation mode for personal travel looks set to arrive. This new mode is the shared autonomous (or fully-automated) vehicle (SAV), combining features of short-term rentals with self-driving capabilities. This investigation examines SAVs ’ potential implications at a low level of market penetration (1.3 % of regional trips) by simulating a fleet of SAVs serving travelers in Austin, Texas ’ 12-mile by 24-mile regional core. The simulation uses a sample of trips from the region’s planning model to generate demand across traffic analysis zones and a 32,272-link network. Trips call on the vehicles in 5-minute departure time windows, with link-level travel times varying by hour of day based on MATSim’s dynamic traffic assignment simulation software. Results show that each SAV is able to replace around 10 conventional vehicles within the 24 mi x 12 mi area while still maintaining a reasonable level of service (as proxied by user wait times, which average just 1.0 minutes). Additionally, approximately 8 percent more vehicle-miles