  An accurate understanding of "when, where and why" of charging activities is
crucial for the optimal planning and operation of E-shared mobility services.
In this study, we leverage a unique trajectory of a city-wide fully electrified
taxi fleet in Shenzhen, China, and we present one of the first studies to
investigate charging behavioral dynamics of a fully electrified shared mobility
system from both system-level and individual driver perspectives. The electric
taxi (ET) trajectory data contain detailed travel information of over 20,000
ETs over one month period. By combing the trajectory and charging
infrastructure data, we reveal remarkable regularities in infrastructure
utilization, temporal and spatial charging dynamics as well as individual
driver level charging preferences. Specifically, we report that both temporal
and spatial distributions of system-level charging activities present strong
within-day and daily regularities, and most charging activities are induced
from drivers' shift schedules. Further, with 425 charging stations, we observe
that the drivers show strong preferences over a small subset of charging
stations, and the power-law distribution can well characterize the charging
frequency at each charging station. Finally, we show that drivers' shift
schedules also dominate the individual charging behavior, and there are
strikingly stable daily charging patterns at the individual level. The results
and findings of our study represent lessons and insights that may be carried
over to the planning and operation of E-shared mobility in other cities and
deliver important justifications for future studies on the modeling of E-shared
mobility services.
