Abstract: Operations of on-demand shared autonomous electric vehicle (SAEV) or “self-driving taxi” service requires careful consideration of idle vehicle dispatch to lower customer wait times, empty travel, emissions, and operating costs. Smart vehicle dispatch strategies are compared using POLARIS, an agent-based model, to show how joint optimization-based strategies can lower wait times and increase daily served trips, compared to SAEV repositioning with charging heuristics. Smart charging to reduce (in)direct energy costs can lower daily electricity costs and emissions damages while serving more passengers than a price-agnostic joint strategy. These studies show the importance of fleet dispatch and charging strategies in improving customer, fleet, and societal outcomes. Bio: Matt Dean is a Ph.D. candidate in UT Austin’s Transportation Engineering Program, where he also received his MS in Civil Engineering. He investigates the large-scale impacts of on-demand mobility, electric vehicles, and ridesharing, as well as transportation and energy sector interdependencies. He has his EIT and is a National Science Foundation Graduate Research Fellow (NSF GRFP).