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Fagnant and Kockelman 1 developed an agent-based model of self-driving conventional taxis on a 10 mi. by 10 mi. grid network (16 km by 16 km), and found that shared vehicles could serve all trips with roughly one-tenth of the number of vehicles, and only 10% additional miles from vehicle relocation, resulting in GHG savings of about 5%. In a subsequent study, the group used MATsim to model a more realistic grid network based on the Austin, Texas metropolitan area, and obtained similar results. 2 Chen et al. extended this model to look at the impact of electrifying this self-driving taxi fleet, and found that taxis with a battery range of 80 miles (129 km) could replace about three vehicles each, while increasing the battery range to 200 miles (322 km) resulted in a replacement ratio of over five to one. 3 A deeper analysis of this model determined that shifting from Level 2 (240V, AC, 7 kW) to Level 3 charging (480V, DC, 50 kW) increases vehicle replacement to 5: 1 and 7: 1, respectively. 4 It was estimated that this electric fleet would cost between $0.40-$0.50/mi.($0.25-$0.31/km) to operate, and capture as much as a third of overall travel mode share. 4

Meanwhile, Bischoff and Maciejewski 5 used the MATSim framework to model 50 electric taxis serving 5% of inner city travel demand in a small city in Poland, with 50 kW fast chargers at each taxi stand. They found that electric taxis can serve demand just as well as conventional vehicles during normal demand conditions, but may incur negative impact during periods of high demand. Building on these results, they developed a cost model to determine the feasibility of a fleet of electric taxis in Berlin …