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Understanding charging dynamics of fully-electrified taxi services using large-scale trajectory data
[article]
2022
arXiv
pre-print
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
arXiv:2109.09799v2
fatcat:ty2gz7rn3nghrodqw5gfbdshxa